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The present study empirically examines the factors accounting for inflation in India in an open economy framework by utilizing the bounds testing approach to cointegration for the 2006: Q3-2019: Q4 period. The findings reveal the existence of a long-run relationship with the household survey-based inflation expectation, real output, narrow money aggregate and interest rate as important determinants of inflation. The study concludes that inflation is well explained by a combination of structural and monetary factors. Notably, the significance of inflation expectation as an important explanatory variable corroborates the utilization of inflation forecast by the RBI as an intermediate target in the flexible inflation targeting framework. In this backdrop, it is imperative for RBI to conduct a high frequency inflation expectations survey of households to account for frequent information updation on the part of certain groups of households.

In this paper, we forecast short-term monthly headline retail inflation in India using daily crowd-sourced food prices and high frequency market-based measures by employing dynamic factors and mixe...

The economic fluctuations in Indian housing markets have been time and again proved to be led by inflation (Granger Cause) (Richa Pandey & V. Mary Jessica, 2020). The purpose of this study is to perform a comparative longitudinal analysis on Global Inflation with a special emphasis on Indian Economy. The study aims to observe the positive cause-effect relationship between the rise of money supply and circulation in the economy and the succeeding rise in housing prices. As Gregory Wolfe theorised, “The inflation of our time is intimately connected with some of its most obdurate ideas, forces, postulates, and institutions and can be overcome only by influencing these profound causes and conditions. It is not just a disorder of the monetary system which can be left to financial experts to redress, it is a moral disease, a disorder of society. This inflation, too, belongs to the things which can be understood and remedied only in the area beyond supply and demand.” Friedman’s permanent income hypothesis suggests that people would change their desired consumption if changes in housing prices affect their expected lifetime wealth. Moreover, an inflationary housing market can be termed essentially, as one of the most major contributors to a nation’s overall inflation (Jared Bernstein, Ernie Tedeschi, and Sarah Robinson, 2021). A comparative longitudinal analysis on inflation can provide significant insights into the evolution of prices over time. By comparing inflation rates across different countries, researchers can identify patterns and commonalities that can help explain the underlying causes of inflation. Additionally, by looking at inflation over a long period of time, this research can help economists, administrators and businesses in identifying periods of high and low inflation to investigate the factors that may have contributed to these changes. In general, inflation is defined as a sustained increase in the price level of goods and services in an economy. Over time, inflation can erode the purchasing power of a currency, as prices for goods and services rise faster than the currency’s value. There are a variety of factors that can contribute to inflation, including increases in the cost of production, changes in monetary policy, and demand-side pressures., {"references":["Richmond Federal Bank 1975 Paper on Monetarist Inflation","Richmond Federal Bank 1981 Paper on Keynesian Inflation","Reserve Bank of New Zealand Discussion Paper No. G98/9 Scott Roger","k-Inflation (String Theory)","Pieter Korteweg, 1979","Thomas M. Humphrey, Federal Bank of Richmond, 1975","Thomas M. Humphrey, Federal Bank of Richmond, 1981","Bronfenbrenner and Holzmann, 1963, p. 599","Jared Bernstein, Ernie Tedeschi, and Sarah Robinson, 2021","Richa Pandey & V. Mary Jessica, 2020"]}

A measure of relative importance of variables is often desired by researchers when the explanatory aspects of econometric methods are of interest. To this end, the author briefly reviews the limitations of conventional econometrics in constructing a reliable measure of variable importance. The author highlights the relative stature of explanatory and predictive analysis in economics and the emergence of fruitful collaborations between econometrics and computer science. Learning lessons from both, the author proposes a hybrid approach based on conventional econometrics and advanced machine learning (ML) algorithms, which are otherwise, used in predictive analytics. The purpose of this article is two-fold, to propose a hybrid approach to assess relative importance and demonstrate its applicability in addressing policy priority issues with an example of food inflation in India, followed by a broader aim to introduce the possibility of conflation of ML and conventional econometrics to an audience of researchers in economics and social sciences, in general., arXiv admin note: substantial text overlap with arXiv:1701.08789

Inflation is the sustained rise in the prices of commodities. Central Banks have the critical responsibility of ensuring price stability; however, every attempt should be made to ensure that price stability should not hit economic growth. Thus, it becomes imperative for Central Banks to determine the key fiscal and monetary factors that have the greatest impact on domestic price levels. Based on these factors, it can tackle the problem of inflation effectively and efficiently. Further, there are several global price indices and factors that need to be factored in while tackling the problem of inflation. The objective of the current study is to empirically determine the macroeconomic factors that play a significant role in influencing inflation in India. The study considers international food and oil price indices amongst other macroeconomic variables such as the fiscal deficit, index of industrial production, exchange rate, MIBOR, and money supply in order to explain inflation. Monthly data for each of the above variables were collected for the research period 2000-10. The study is based on Vector Auto-Regressive modeling. The Augmented Dickey-Fuller Unit Root Test was performed to test for stationarity of all of the time-series data. The results of the Granger causality tests indicate that fiscal indicators such as fiscal deficit and international factors such as international food and oil price indices play a significant role in influencing inflation. The research outcomes conform to the results of several earlier studies. Key Words:Inflation, fiscal and monetary factors, macroeconomic factors, vector autoregressive modeling, Granger causality test

This paper investigates the time-varying effects of monetary policy on aggregate, sectoral, and disaggregate inflation in India from 1997 to 2017 using a large dataset of 439 variables. We find that the effectiveness of a contractionary monetary policy in controlling aggregate inflation has improved over time. This improvement in the policy's effectiveness can be attributed to better transmission through credit and asset price channels. In investigating disaggregate inflation, we find that a contractionary monetary policy is more effective in reducing inflation in the manufacturing sector than in the agricultural sector. Further, the sacrifice ratios in all manufacturing sectors have improved over time. However, the commodities prices of some sectors respond positively after a monetary contraction, which demonstrates the presence of a cost channel in the Indian economy. Our findings suggest that the monetary authority in India should have an interest rate rule that incorporates sectoral inflation and reacts to each with different intensity.

A comprehensive strategy for price stability, particularly for the long-run, requires coordination between monetary and fiscal policy. To our knowledge, the fiscal initiative to control inflation in India is abstracted. The targets and executions of the fiscal policy of different state governments are independent, lop-sided, and also distinct from the fiscal stance of the central government. Besides, the fiscal policy of the central and the state governments are not consistent with the monetary policy of the Reserve Bank of India. Under this backdrop, this paper examines the extent of fiscal variable, trade openness in addition to structural and monetary policy variables impacting inflation in India since the 1980′s. The paper confirms that public debt is inflationary; while openness is anti-inflationary particularly the consumer price inflation is concerned. Significant impact of the money growth, real interest rate, real effective exchange rate, and the output gap in consumer and wholesale price inflation is also established. The paper concludes that apart from the monetary management, anti-inflationary fiscal policy and comprehensive policy for the real sector and external sector are also essential to stabilize inflation for the long-run. Prolific monetary-fiscal policy coordination in India is a fantasy.

The nexus between inflation and trade openness has been one of the major concerns among the researchers and policy makers in both developed and developing economies. The exact relationship between inflation and openness is still in ambiguity. Various studies have been done for different countries and regional groups using different methodologies to measure the relationship between openness and inflation, but all remained in vain. Although there are different views regarding this relationship, most of the empirical studies supported the Romer’s hypothesis (Q J Econ 108(4):869–903, 1993) of an inverse association between openness and inflation in the economy. The present study has made an attempt to examine the factors influencing the price level, especially trade openness, in India from 1974–1975 to 2015–2016. For empirical investigation, the study has employed autoregressive distributed lag (ARDL) model bounds testing approach to co-integration (Pesaran et al., J Appl Econ 16(3):289–326, 2001). The obtained results revealed the presence of positive relationship between inflation and trade openness in India, which negates the Romer’s hypothesis.

An augmented P-Star model is estimated and tested to identify the drivers of inflation in India. The model includes monetary and non-monetary factors, demand-pull and cost-push factors, and domesti...

A commonly held belief in the 1970s was that price indices rise because of temporary noise, and then revert after a short interval (Cecchetti and Moessner, 2008). Accordingly, policy should not respond to the inflation because of these volatile components of the price indices. This led to the development of the concept of core inflation (Gordon, 1975), which is headline inflation excluding food and fuel inflation. It was strongly believed that in the long run, headline inflation converges to core inflation and that there are no second round effects (that is an absence of core inflation converging to headline inflation). In recent years, however, major fluctuations in food inflation have occurred. This has become a major problem in developing countries, such as India, where a large portion of the consumption basket of the people are food items. Against this backdrop, in the present paper, an attempt is made to measure the second round effects stemming from food inflation in India using the measure of Granger causality in the frequency domain of Lemmens, Croux and Dekimpe (2008). The results of empirical analysis show significant causality running from headline inflation to core inflation in India and as a result, the prevalence of the second round effects. They also show that food inflation in India is not volatile, and that it feeds into the expected inflation of the households, causing the second round effects. This calls for the Reserve Bank of India to put greater effort in anchoring inflation expectations through effective communication and greater credibility.

The purpose of this study is to examine the long-run and short-run impact of crude oil price and exchange rate shocks on domestic inflation in India within the framework of the Autoregressive Distributed Lag (ARDL) model. The results show that the exchange rate and oil price shocks significantly influence domestic inflation during the study period (April 1994 to February 2018). Further, the breakpoint unit root test revealed the severe impact of the 2008 financial crisis on inflation in India. The findings show that any move to scale down fuel subsidies will escalate cost-push inflation severely, as the country is an energy-dependent economy. So, policymakers shall stabilise the impact of these shocks through suitable monetary policy actions.

How do mark-up shocks affect food inflation in India? The rent seeking activities of agents in both wholesale and retail marketing of food, and the lack of a competitive food market and required infrastructure, often cause large positive shocks to mark-ups. This paper estimates the contribution of these mark-up shocks at both wholesale and retail level in food inflation. The study finds moderate but significant pass through of mark-up shocks in food inflation after controlling for other factors. Against the backdrop of building a competitive national market for food to promote greater competition and to stabilise large shocks to mark-ups, this paper makes a contribution towards understanding the extent to which stabilisation of mark-up shocks at both wholesale and retail level can lower wholesale and retail food inflation in the country. Keywords: Food inflation, India, Mark-up shock, National market for food, SVAR

This paper examines the factors that effect the monthly inflation rate in India using monthly data from January 2010 to October 2020. Two multiple linear regression models, with and without interaction terms, using least squares method for coefficient estimation have been used to find out which factors have a direct effect on the monthly inflation rate. The results indicate that the Gross Domestic Product (GDP), the interaction between exchange rate and M1 money supply; interaction between bank rate and GDP, and interaction between bank rate and M1 money supply; have a significant influence on the monthly inflation rate in India.

COVID-19 has wreaked havoc on the economy in a variety of ways. The effect of the novel coronavirus on various aspects of the Indian economy and the economies of South Asian countries is investigated in this research paper. This study's main goals are as follows: 1. To understand impact of COVID-19 on overall Indian Economy and South Asian countries. 2. To know impact of COVID-19 on different sectors and 3. To find out the GDP growth rate of the economy. India's economy is the world's fifth highest, with a gross domestic product (GDP) of $2.94 trillion, surpassing the United Kingdom and France to take fifth place in 2019. India's GDP is also $10.51 trillion in purchasing power parity (PPP), surpassing Japan and Germany and placing India as the world's third largest contributor to GDP. According to data released by the International Monetary Fund, India's GDP growth premium over emerging economies (EMs) is expected to drop to a seven-year low of 1.1 percent in the current fiscal year 2019-20, owing to poor investment, credit problems, currency volatility, slower demand growth, and increasing inflation (IMF). The study depicts the actual GDP growth rate when taking into account market inflated final goods and services rates. According to the ADB's COVID-19 pandemic outlook, inflation in the sub-region will be moderate, averaging 4.1 percent in 2020, as food inflation in India eases due to improved agriculture. Because of this minor inflationary rate in South Asia, the pandemic would cause the real GDP growth rate in all countries to slow down. With subsidies and price caps on basic goods, the Maldives' remarkably low inflation will remain the same, despite an expected deterioration in the recommended requirements. Pakistan, on the other hand, would experience double-digit inflation due to rising food prices. Annual inflation in South Asian countries increased significantly from 3.3 percent in 2019 to 2.4 percent in 2020, with real GDP rising by 6.6 percent. According to Central Statistics, India's nominal GDP reached 728.6 USD billion in December 2019, and its GDP deflator (implicit price deflator) increased by 2.9 percent. In March 2019, India's GDP per capita was 2,044.6 USD. Steps taken to halt its spread, such as state lockdowns, halted economic activity and could have a significant effect on both consumption and investment.

This chapter attempts to examine the exchange rate pass-through (ERPT) to consumer prices under inflation targeting (IT) framework in India. The chapter uses monthly data from the period January 2011 to October 2019 for the empirical investigation. The vector auto-regression (VAR) model is employed with variables on exchange rate, oil price, output, policy interest rate, and consumer prices index for the empirical analysis. The sample period is subdivided under two scenarios, pre-inflation targeting period (January 2011–October 2015) and post-inflation targeting period (November 2015–October 2019). The study finds that there is a significant decline of exchange rate pass-through under inflation targeting regime as compared to its previous regime, i.e., the multiple indicator approach regime. This finding is in line with an important study in Indian context by Patra et al. (Non-linear, asymmetric and time-varying exchange rate pass-through: Recent evidence from India. Reserve Bank of India, Working paper (02/2018), Mumbai, 2018). The study also supports the Gagnon and Ihrig (International Journal of Finance and Economics 9:315–338, 2004) theory which maintains a decline in exchange rate pass-through under inflation targeting framework. The chapter suggests that the decline in exchange rate pass-through via imported inflation may be helpful for monetary policy to achieve the target of inflation in India.

Хронический дефицит государственного бюджета и рост уровня цен становятся предметом активных обсуждений как экономистов, так и представителей власти. Результаты многочисленных исследований, посвященных анализу данной темы, в контексте развитых и развивающихся стран неоднозначны, поскольку при анализе используются различные методы оценки, выборки временных периодов и переменных и др. В настоящей статье исследуется взаимосвязь между бюджетным дефицитом и инфляцией в Индии в период с 1980-1981 по 2016-2017 гг. Для этой цели были использованы модель авторегрессии и распределенного лага (ARDL) и нелинейная модель авторегрессии и распределенного лага (NARDL). В результате применения модели ARDL линейная связь между бюджетным дефицитом и инфляцией в контексте Индии не обнаружена. Однако эмпирические результаты, полученные при помощи NARDL, подтвердили существование нелинейной связи между бюджетным дефицитом и инфляцией в долгосрочной перспективе и отсутствие связи между денежными ресурсами и инфляцией. Данный результат подтверждает положения фискальной теории уровня цен, согласно которой государственный долг и налоговая политика определяют уровень цен, а денежно-кредитная политика играет лишь косвенную роль. Следовательно, при планировании налогово-бюджетной политики следует сосредоточить внимание на сокращении бюджетного дефицита. В то же время, Резервный банк Индии (RBI) должен сфокусироваться на регулировании процентной ставки по ссудам. Данные меры необходимы, чтобы обеспечить сочетание налогово-бюджетной и денежно-кредитной политики для контроля инфляции в Индии. The chronic government deficit (fiscal deficit) and increase in the price level (inflation) have become major concerns for economists and policymakers. While numerous studies have examined the twin problems of the fiscal deficit and inflation for both developed and developing economies, their results are inconclusive due to different estimation techniques, chosen time periods, selection of variables, etc. Therefore, we examined the fiscal deficit-inflation nexus in India for the period from 1980-81 to 2016-17 by employing the Autoregressive Distributed Lag (ARDL) and Nonlinear Autoregressive Distributed Lag (NARDL) approaches. The results of the ARDL approach found no evidence of linear relationship between fiscal deficit and inflation in the Indian context. Further, the empirical findings of the NARDL model confirmed the nonlinear relationship between fiscal deficit and inflation in the long run and no association between money supply and inflation, supporting the ideas of the Fiscal Theory of the Price Level (FTPL) in the case of India. FTPL postulates that public debt and taxation policies drive price level; monetary policy has an indirect role only. Therefore, fiscal policymakers should focus on reducing fiscal deficits. Simultaneously, the Reserve Bank of India (RBI) should regulate lending interest rate so that a mix of fiscal and monetary policies can be applied for controlling inflation in India.

In this study, we proposed a 2-stage hybrid approach for financial time series forecasting wherein chaos is modeled in stage-1 followed by forecasting is accomplished using machine learning and deep learning algorithms in stage-2. The effectiveness of the proposed hybrid is tested on forecasting Consumer Price Index Inflation of Food & Beverages, Fuel & Light, and Headline in India. This is a first-of-its-kind study where chaos is modeled and deep learning is employed in forecasting macroeconomic time series. From the results, it is inferred that Chaos + Machine learning hybrids yielded better forecasts than pure machine learning algorithms without Chaos in terms of Symmetric Mean Absolute Percentage Error (SMAPE), Theil’s U statistic and Directional statistic across all the data sets. A deep learning model namely, Long Short Term Memory (LSTM) was also employed but without much success. The results of 2-stage hybrid models are compared with models without accounting for chaos. The results are encouraging and these hybrids can be applied to predict other financial time series.

Purpose – Among the many factors fueling the inflationary tendencies in an economy such as monetary shocks, structural shocks, demand shocks, external shocks and demographic changes, the issue of inflation (INF) has also been found to be related to fiscal policy decisions of the government. The purpose of this study is to investigate the inflationary tendencies in India particularly from the fiscal point of view. The study also examines the influence of other potential determinants such as output growth rate, interest rate, tradeopenness (TO) and oil price inflation (OPI). Design/methodology/approach – To examine the dynamic nature of association between fiscal deficit and inflation, the study applies the Toda-Yamamoto (1995) test and Breitung and Candelon (2006) test to investigate the nature of causality in time and frequency domain frameworks. In addition, to scrutinize the possibility of a long-run association, that too from an asymmetric point of view, the study applies a Non-linear Autoregressive Distributed lag model (NARDL) given by Shin et al. (2014). Finally, non-linear cumulative dynamic multipliers are used to trace the traverse between disequilibrium position of short-run and subsequent long-run equilibrium of the system. Findings – The authors found a unidirectional causality from fiscal deficit to inflation in case of time domain analysis and no feedback causality is reported. However, in case of frequency domain design, causality from fiscal deficit to inflation is found at low frequencies only, i.e. no short-run causality is established and hence dynamic nature of the relationship between the two variables is vindicated. Using NARDL model, the results document the existence of an asymmetric long-run direct association between fiscal deficit and inflation. However, an increase in deficit is found to be more inflationary and a decrease affects the inflation with a lower magnitude. The asymmetric impact of fiscal deficit on inflation can be explained through the existence of liquidity constraints, consumption-investment downward inflexibility and the downward price stickiness. Contractionary monetary policy action is found to be more effective than an expansionary one, signifying the asymmetric influence of monetary policy actions on the inflation of India. Similarly, in a supply-constrained economy with downward price rigidity, the authors found an asymmetric impact of output growth and output decline on inflation. As regard to the trade-openness, although an asymmetry is reported, the signs refute the validation of Romer (1993) hypothesis. Finally, the impact of oil price inflation on the inflationary pressures is according to theory but the coefficients are devoid of statistical significance. Practical implications – These results indicate some important policy recommendations. Fiscal consolidation strategy should be executed in an appreciable manner to achieve the sound fiscal health and lower INF. The disciplined fiscal strategy would also be imperative for an effective monetary policy.Monetary authorities should possess noticeable credibility to manage the macroeconomic system and policy stances should be implemented according to requirements of the economy. Growth in output should be encouraged to have twofold benefits to the economy – reducing INF on the one hand and fiscal deficits on the other. Originality/value – The study contributes to the existing literature in the following ways. First, taking note of dynamic nature of the relationship between these two variables, the study examined the deficit INF nexus in a dynamic and asymmetric framework. The novelty of the study is ensured by the very nature of it is the first study in case of India to identify the fiscal INF in an asymmetric configuration. The authors applied a NARDL model, given by Shin et al. (2014) to examine the existence of any cointegrating relationship in an asymmetric paradigm. Second, the nature of causality between fiscal deficit and INF has been examined in a time domain and FD framework to portray precisely the casual interactions between these two variables in the short-run and long run. The study will, therefore, enrich the existing literature along the asymmetric lines. Proposito – Entre los muchos factores que alimentan las tendencias inflacionarias en una economia, como los choques monetarios, estructurales, de demanda, externos y cambios demograficos, tambien se ha encontrado que el tema de la inflacion (INF) esta relacionado con las decisiones de politica fiscal del gobierno. El proposito de este estudio es investigar las tendencias inflacionarias en India, particularmente desde el punto de vista fiscal. El estudio tambien examina la influencia de otros determinantes potenciales como la tasa de crecimiento de la produccion, la tasa de interes, la apertura comercial (TO) y la inflacion del precio del petroleo (OPI). Diseno/metodologia/enfoque – Para examinar la naturaleza dinamica de la asociacion entre el deficit fiscal y la inflacion, el estudio aplica la prueba de Toda-Yamamoto (1995) y la prueba de Breitung y Candelon (2006) para investigar la naturaleza de la causalidad en marcos de dominio de tiempo y frecuencia. Ademas, para escudrinar la posibilidad de una asociacion a largo plazo que, tambien desde un punto de vista asimetrico, aplica un modelo de retardo distribuido autorregresivo no lineal (NARDL) dado por Shin et al . (2014). Por ultimo, se utilizan multiplicadores dinamicos acumulativos no lineales para trazar la trayectoria entre la posicion de desequilibrio del sistema a corto plazo y el posterior equilibrio a largo plazo. Hallazgos – Los autores encontraron una causalidad unidireccional del deficit fiscal a la inflacion en el caso de un analisis en el dominio del tiempo, y no se reporta causalidad de retroalimentacion. Sin embargo, en el caso del diseno del dominio de frecuencia, la causalidad del deficit fiscal a la inflacion se encuentra solo en frecuencias bajas, es decir, no se establece una causalidad a corto plazo y, por lo tanto, se justifica la naturaleza dinamica de la relacion entre las dos variables. Utilizando el modelo NARDL, los resultados documentan la existencia de una asociacion directa asimetrica a largo plazo entre deficit fiscal e inflacion. Sin embargo, un aumento del deficit resulta mas inflacionario y una disminucion afecta la inflacion con menor magnitud. El impacto asimetrico del deficit fiscal sobre la inflacion puede explicarse por la existencia de restricciones de liquidez, la inflexibilidad a la baja del consumo-inversion y la rigidez de los precios a la baja. Se encuentra que la accion de politica monetaria contractiva es mas efectiva que una expansiva, lo que significa la influencia asimetrica de las acciones de politica monetaria sobre la inflacion de India. De manera similar, en una economia de oferta restringida con rigidez de precios a la baja, los autores encontraron un impacto asimetrico del crecimiento y la disminucion de la produccion en la inflacion. En cuanto a la apertura comercial, aunque se reporta una asimetria, los signos refutan la validacion de la hipotesis de Romer (1993). Finalmente, el impacto de la inflacion del precio del petroleo sobre las presiones inflacionarias es segun la teoria, pero los coeficientes carecen de significacion estadistica. Implicaciones practicas – Estos resultados indican algunas recomendaciones politicas importantes. La estrategia de consolidacion fiscal debe ejecutarse de manera apreciable para lograr la solidez fiscal y un menor INF. La estrategia fiscal disciplinada tambien seria imperativa para una politica monetaria eficaz. Las autoridades monetarias deben poseer una notable credibilidad para administrar el sistema macroeconomico y las posturas de politica deben implementarse de acuerdo con los requisitos de la economia. Debe alentarse el crecimiento de la produccion para que tenga dos beneficios para la economia: la reduccion del INF, por un lado, y los deficits fiscales, por el otro. Originalidad/valor – El estudio contribuye a la literatura existente. En primer lugar, tomando nota de la naturaleza dinamica de la relacion entre estas dos variables, el estudio examino el nexo INF deficitario en un marco dinamico y asimetrico. La novedad del estudio esta asegurada por la propia naturaleza del mismo. Es el primer estudio en el caso de India que identifica el INF fiscal en una configuracion asimetrica. Los autores aplicaron un modelo NARDL, proporcionado por Shin et al. (2014) para examinar la existencia de cualquier relacion de cointegracion en un paradigma asimetrico. En segundo lugar, la naturaleza de la causalidad entre el deficit fiscal y el INF se ha examinado en un marco de dominio del tiempo y DF para representar con precision las interacciones casuales entre estas dos variables a corto y largo plazo. El estudio, por lo tanto, enriquecera la literatura existente en lineas asimetricas.

This paper provides a narrative of Indian monetary policy since the North Atlantic Financial Crisis (NAFC) in the mid‐2008 till the current period. The period 2009–2013 was dominated by the joint monetary and fiscal stimuli of the Indian authorities prompted by the NAFC. These, along with some structural shocks and a hands‐off attitude in forex market intervention, could have had their role in rising inflation and external account instability (leading up to the taper tantrum episode). In such a backdrop, after considerable discussion during 2013–2014, a Monetary Policy Framework Agreement was signed between the Government of India and the Reserve Bank of India on February 20, 2015 that formally adopted flexible inflation targeting (IT) in India. While the IT regime so far has coincided with significant reduction in inflation in India, the atmosphere has been benign. Now that fuel prices have started moving in the north‐east direction, the government has proposed a revised framework for the minimum support price in the Union Budget for 2018–2019 and fiscal slippages have started happening, it remains to be seen whether IT can wither more rough weather in the days to come. Finally, in recent years, Indian monetary policy has been dominated by two significant events: the emergence of significant deterioration of Indian public sector balance sheets, and the demonetization episode in November 2016. Monetary policy in both of these periods wrestled with fashioning an appropriate strategy for managing the impossible trinity.

The present paper attempts to explore the nature, trends and patterns of inflation in India during 1980-2016. The selected time period has been trifurcated purposively into three-time spans namely, pre-reform period (1980-90), after reform period (1991-2000) and subsequent period (2001-16). The endeavour of the paper is to examine the dynamics of inflation over the three-time spans from 1980-2016 in the Indian economy. It has been found that the inflation, based on WPI and CPI, is continuously rising since 1980. Up to 1995, the trend in CPI and WPI were same and there was no significant difference between them. However, after 1995, CPI has recorded larger growth as compared to WPI. Such trend has also continued in the subsequent period. The study reveals that this trend may be attributed to change in the composition of WPI and CPI since weights of primary articles have declined in WPI whereas such weights have registered a considerable increase in the categories of manufacturing, fuel and power. The shift in weights overtime provides us with an indicator of the changing production and use pattern of the commodities in the Indian set up. Further, the weights of food items have reduced overtime in case of CPI and such weights have been increased in respect of clothing, housing and fuel. The changes witnessed in weights of CPI are indicators of a growing economy. This study further contributes in the available literature by comparing the patterns of Inflation in Pre and Post-reform Period.

This paper brings out the salient features of different measures of inflation in India. Before adopting the flexible inflation targeting framework, RBI focused on using Wholesale Price Index (WPI) as the measure of headline inflation. Consumer Price Index for Industrial Workers (CPI-IW) was the widely used measure of CPI inflation. International practice however, suggests the use of CPI as the measure of headline inflation. There are also limitations of using WPI as a measure of inflation. Hence, Central Statistics Office (CSO), launched a new measure of CPI, known as CPI-Combined which incorporates all Indian rural and urban households. Stylized facts used in the paper show that inflation dynamics in India is characterised by a divergence between CPI-IW and WPI indices. Against this backdrop, the paper examines Granger Causality between the two indices in a Vector Auto Regressive framework. Results of the study indicate that there is bidirectional causality between the two indices which does not get affected even during the period of global financial crisis, when the divergence between the two indices was observed for the longest duration.

Food prices in India have increased on an average by more than 10% annually over the period 2006–2007 through 2013–2014. However, unlike the earlier years, food inflation was not just a supply driven phenomenon caused by such factors as adverse climate conditions. It is important to note that during this period it was prices of the so called protein rich items like pulses, fruits, vegetables, eggs, meat, fish and milk that marked high rates of increase. It is thus argued that food inflation has turned structural in the sense that it has prominently been driven by changing demand structure. Keeping this in mind, the current study is intended to focus on the causes of high inflation in protein based items. To this end, following the structuralist approach, we take note of the market structure and long term perspective of the problem. The study covers the period, 1980–1981 through 2013–2014 on an annual basis. Our results confirm that there is the dominant impact of demand factors in determining protein inflation. International food prices are also found to be significant in shaping domestic food prices. For ensuring price stability, demand side management without jeopardizing growth turns out to be considerably important. It is in view of this that sustainable way turns out in improving the supply conditions.

Average food inflation in India during 2006–2013 was one of the highest among emerging market economies, and nearly double the inflation witnessed in India during the previous decade. In this paper, we analyse the behaviour and determinants of food inflation over the recent past. Our main findings include that recent surge in food inflation in India is a result of various factors. On the cost side, agricultural wage inflation is found to be a universal driver of food commodities inflation, as well as the aggregate food inflation. The contribution of agricultural wages has increased significantly in the post Mahatma Gandhi National Rural Employment Act era. Fuel inflation has a moderate impact on food inflation and the effects vary across commodities. Our analysis indicates limited role of fuel and international prices, except for in tradeables. Finally, results suggest significant pass-through effects from food to non-food and to the headline inflation.

Average food inflation in India during the period 2006–2013 was one of the highest among emerging market economies and nearly double the inflation witnessed in India during the previous decade. An often-cited hypothesis argues that the surge in food inflation during this period was driven by rising demand for high-value food products due to higher per capita income and diversification of Indian diets. In this article, we test the validity of this hypothesis by estimating the expenditure elasticity and then calculating the aggregate demand using data from household survey conducted by the National Sample Survey Organisation (NSSO). Our results show that in recent years, estimated demand has exceeded supply of all major food products, barring fruits. Moreover, empirical estimates indicate that the demand–supply gap is an important driver of rise in food prices, along with other factors such as minimum support prices, global prices, fiscal deficit and agricultural wages. JEL Classification: E31, E37, Q11

Fiscal deficit and inflation are the two major macroeconomic problems confronting the Indian economy. Although it had manifested in various degrees earlier, these problems escalated after the recent global financial crisis. It has always been criticized that fiscal deficit will adversely impact the level of inflation. This critique has been proved and validated by many existing studies in the context of India. This paper strives to track the channels of transmission through which fiscal deficit has passed on and impacted the level of inflation in India. Based on theoretical and empirical literature, this study identifies four transmission channels, namely consumption expenditure channel, money supply channel, import channel and interest rate channel. By adopting structural vector autoregression model, it has been found that the fiscal deficit transmission mechanism is clearly evident with regard to consumption channel, money supply channel and import channel but not the interest rate channel.

In this paper we bring out the performance of the Indian economy, and review the approach of macroeconomic policy especially demand management in the Indian economy. After the shock of the Global Financial Crisis (GFC), India’s economy did not dip much due to the well-directed fiscal stimulus by the government early on. The government could persuade an RBI which was still “fighting” a supply side inflation to expand liquidity to at least reverse the sharp fall in liquidity that had taken place due to the contagion and capital flight brought about by the GFC. However, as the fiscal stimulus was being withdrawn from 2011-12, the RBI tightened to raise interest rates, which from 2012-13 put brakes on the economy. Tight monetary conditions continued almost until 2016. The RBI saw rising inflation not only in the non-core part of the CPI, but also on the core, thereby “necessitating” this counter action, in its view Additionally the RBI also in “defending” the currency kept higher than desirable interest rates. Closer examination would reveal that much of the rise in the core inflation was spurious since it was on account of the house rents “going up” due the 6th Pay Commission award which was first notified for the government employees in mid-2009. The spurious impact on the core would have been as high as 4%. [Even today in the midst of the COVID-19 Crisis, the large rise in the core now on account of the delayed 7th Pay Commission implementation confuses not only the RBI but the media as well]. The year 2013-14 also saw the RBI move to “inflation targeting”, and to continued lightening which kept interest rates record high and created a large fisher open which attracted expensive gross foreign equity capital inflows, though on a net basis the flows were incomparably small in relation to the period of high growth before the GFC – the “Tiger” Period (2003-04 to 2007-08). The “taper tantrum” saw even further rise in interest rates. More importantly for a period as long as 10 years with only short breaks, the low end bond yields remained well above the repo rate, signifying that the repo windows were prematurely closed and the RBI was de facto carrying out credit rationing as well, negating the repo rates as “policy rates”. From 2014-15, and only after the economy had slowed down considerably that the interest rates could begin to come down, and even then the anomaly of the market rates being higher than the “policy” remained. Inflation targeting brought with it many problems for the RBI and the fact that forecasted inflation (conditional on the RBIs own measures) was always higher than realized inflation by a wide margin, which seriously questions the RBI’s approach to monetary policy. Similarly, its expectations surveys are off the mark systematically by a wide margin. Even more importantly the RBI’s propensity to react to current CPI inflation than to forward looking core inflation means that financial markets (over the longer term and longer maturity instruments) do not react to even the lowering of the low end rates, since this approach of the RBI makes the future very uncertain, and therefore the first leg of the transmission is hurt by the modus operandi of the RBI itself. Moreover, there is very little support to the RBI’s contention that even a supply side inflation needs to fought from the demand side to prevent inflationary expectations from building up, since not only have expectations (correctly measured) not shown any secular trend except downwards, but food inflation which drove everything else during this period, can hardly be affected by demand side measures, since the income elasticity of food is very small, even for a poor country like India now that there are few people below the poverty line. The point that India may be at a phase (encountered by all densely populated countries that pierced the middle income barrier) when the terms of trade need to rise in favour of agriculture, to bring the agricultural sector into the home market in a vigorous way, has missed the RBI On the fiscal side a variety of measures adversely affected investment, and animal spirits. The ‘policy paralysis’ during the last years of the UPA government was the turning point. However, with the Modi-I government the large reduction in anti-poverty programmes and especially the Mahatma Gandhi National Rural Employment Guarantee Scheme (MNREGS) allocations, the underspending from the budgetary provisions in the first two budgets of the Modi government (as a side effect of the extreme centralization of power in the PMO), besides the “unconditional” commitment to the fiscal deficit targets, further contributed to the demand decline. From the third year onwards of Modi-I the policy and action uncertainties including those let loose on the automobile sector took their toll. The talk of banning diesel vehicles was highly damaging to the industry, that had just made the transition to being able to meet Bharat VI norms. From 2012-13 growth had fallen but the official 2011-12 series did not reflect the same. Growth from 2012-13 to 2017-18 could not have been more than 5.5% p.a. most probably under 5%. And the investment growth rate especially of the private sector had all but collapsed. Investment share in GDP came down to a mere 32% of GDP from its high levels of 36 to 37% over the “Tiger” period. Public investment in infrastructure often directed sub-optimally from the productivity and value creating standpoint, was dominant. Private investment saw the longest period of near stagnation, ever since its faster growth from the mid-eighties and its acceleration after the Great Liberalisation (GL) of 1991-92, 92-93. The economy seemed to more than recover from the decline brought about by the demonetization, from late 2017 onwards, but the growth of around 7.8 % over three quarters, quickly gave way to a slow down reaching as low a rate as 3% on the eve of the COVID-19 Crisis. While nearly all the programmes of the Modi government were about increasing public and social value, the poor capability of the government at the organizational, coordination, and strategy and design levels cheated the NDA of transformative second generation reforms. Instead, most of these fizzled out. There was little of the creativity of the earlier National Highway Development Programme (NHDP) nor of the Prime Ministers Gram Sadak Yojyan (PMGSY) under Vajpayee, when the government had the wisdom to accept and implement a well-crafted NHDP that actually came from the IDFC. Only the Direct Benefit Transfers were improvements. But even here the realized gains were far below the potential. The task of combining (structural and tax) reforms with macroeconomic demand management in a positive way proved beyond the capability of the government. Thus even excellent and politically difficult reform like the introduction of GST, while largely successful in itself, led to increased effective tax rates (precisely because it improved compliance) adding to the downward pressure on demand, when measures to counter act the same could have been used. Bank lending, which was always a problem given governmental interference and a “laundry-list approach” to regulation pursued by the RBI, went from bad to worse. Much of the lending during the period of the fiscal stimulus was hurried, and began to worry the PSU banks once the slowdown happened. The slowdown itself contributed to their bleak situation which in turn negatively affected whatever little transmission they could have affected. The delay in their recapitalization affected the Non-Banking Financial Companies (NBFCs) and the real estate sector to create a gridlock on lending. The frameworks for private investment in infrastructure (except in the highways) were inappropriate The external sector was benign but the government hardly used the opportunity of falling oil prices. This was because of its single minded pursuit of reducing the fiscal deficit often with the limiting perspective of managing a family budget. An entirely uncoordinated and knee-jerk approach, and literal interpretation of the prime minister’s slogan and programmes, by the bureaus meant that many ambitious programmes hardly went beyond tokenism. The steady growth of the world economy did not positively affect India through export growth, as much as it could have, since real effective exchange rates continued to be high relative to its competitors in East Asia that now included Vietnam.

The most important economic controversies among monetary authorities, policy makers and economists is “The relationship between inflation and economic growth”. The empirical and theoretical evidences provide three types of relationship between inflation and economic growth - negative, positive and none. Although the relationship between inflation and economic growth has been widely examined and investigated over the years, still this is a burning issue which hinders the economic growth of a country. In this paper, it is proposed to investigate the relationship between Economic growth and Inflation in India during the period 1980-2016 using various cointegration techniques and correlation.

In this paper, we investigate the short run and long run causal relationship between wholesale price index (WPI) and consumer price index (CPI) in India over the period from 1994 April to 2015 August. Using a linear cointegration and a nonlinear time series model of threshold cointegration with asymmetric error correction model and spectral Granger causality approach, the study attempts to find the linear and nonlinear cointegration relationship between WPI and CPI in India. Empirical results reveal the non-existence of linear cointegration between the WPI and CPI indices in India. Moreover, using consistent threshold autoregressive (C-TAR) and consistent momentum threshold autoregressive (CM-TAR) model, we find the evidence of non-linear cointegration between WPI and CPI in India over the period from 1994 to 2015. The consistent M-TAR model indicates the presence of threshold cointegration between WPI and CPI, which further suggests the consistent inflationary trends after 1995 in India due to rising per capita income and other macroeconomic indicators. Furthermore, results indicate that WPI and CPI are cointegrated with threshold error correction adjustment, and the adjustment towards long-run equilibrium is asymmetric. This further suggests that WPI and CPI respond differently to positive and negative deviations from the long-run equilibrium after the threshold level. Empirical results further indicate that adjustment towards longrun equilibrium tends to persist more for negative deviations and respond more quickly towards positive deviations. The spectral granger causality results do not reveal the causality from WPI to CPI. However, the Granger causality from the asymmetric error correction model reveals the unidirectional causality, which indicates that CPI Granger causes WPI, support the demand-push inflation in India. CPI Granger causes WPI at very low and high frequencies, which takes an average wavelength of more than 3.6 quarters time in a year. Furthermore, empirical results reveal that WPI and CPI reach equilibrium asymmetrically after the threshold level of the two percentages. In sum, results suggest that the Indian policymakers can emphasis on the demand side rather than supply-side inflation to control the level of inflation after the desired threshold level. Moreover, the central bank of India would give importance to control the unwarranted inflationary trend, which has been caused due to the CPI-based demand-side inflation.

One major source of inflation in India is her import of intermediate inputs. In the modern globalized world, where India is deeply integrated with the world economy, exchange rate affects inflation through various channels. This chapter attempts to gauge the extent of exchange rate pass through to inflation. Using the co-integration framework, this chapter finds considerable evidence of imported inflation in the long run, almost 40%–74% for CPI-IW. At the same time, we also discern evidence of short-run price stickiness of CPI-IW. However, for CPI-AL, the extent of pass-through is a meager 14%. This is due to the fact that CPI-IW gives more weightage to imported components while CPI-AL gives more weight to food and clothing, which are mainly domestically produced.

In the recent past, several attempts by the RBI to control inflation through tight monetary policy have ended up slowing the growth process, thereby provoking prolonged discussion among academics and policymakers about the efficacy of monetary policy in India. Against this backdrop, the present study attempts to estimate the causal relationship between monetary policy and its final objectives; i.e., growth, and controlling inflation in India. The methodological tool used is testing for Granger Causality in the frequency domain as developed by Lemmens et al. (2008), and monetary policy has been proxied by the weighted average call money rate. In view of the fact that output gap is one of the determinants of future inflation, an attempt has also been made to study the causal relationship between output gap and inflation. The results of empirical estimation show a bi-directional causality between policy rate and inflation and between policy rate and output, which implies that the monetary authorities in India were equally concerned about inflation and output growth when determining policy. Furthermore, any attempt to control inflation affects output with the same or even greater magnitude than inflation, thereby damaging the growth process. The relationship between output gap and inflation was found to be positive, as reported in earlier studies for India. Furthermore, the output gap causes inflation only in the short-tomediumrun.

This study uses P‐star model to examine the role of money in explaining inflation in India. In particular, we compare the performance of traditional Phillips curve approach against P‐star model in forecasting inflation. Moreover, the study estimates P‐star model using the alternative measures of money such as simple sum and Divisia M3, to examine the relevance of aggregation theoretic monetary aggregates in explaining inflation. The empirical results indicate that P‐star model with real money gap has an edge over traditional Phillips curve approach in forecasting inflation. More importantly, we found that the P‐star model estimated with Divisia real money gap performs better than its simple sum counterpart. These empirical findings suggest that the changes in real money gap play a crucial role in explaining inflation in India.

In the standard approach of building prediction models, macroeconomic data is matched with monthly or quarterly or annual aggregates of financial series, since macroeconomic data are typically available at those frequencies. Such aggregation leads to the loss of useful forward-looking information of financial data. This is so because financial data are usually observed with higher periodicity than monthly data. Recent empirical evidence suggests that a Mixed Data Sampling (MIDAS) regression technique improves the predictive power of the models that incorporates data of different frequencies. In this article, we propose an autoregressive MIDAS model for forecasting monthly inflation in India using daily treasury yield information. Empirical results show that the proposed model has better predicting power over forecasting inflation in India.

This paper examines the relative role of structural and monetary factors in the variation of inflation in India over the period 1996–1997:Q1 to 2013–2014:Q4. The paper finds that both the monetary factors and the output gap has significant role. The role of the output gap in inflation is found more prominent than the monetary factors like broad money growth, interest rate and change in exchange rate. The depreciation of exchange rate and broad money growth stimulates inflation where as the interest rate is identified as an anti-inflationary monetary instrument. In view of a comprehensive policy for price stability, it is imperative to know the role of sectoral output gap in inflation. The paper, therefore, enquires the relative role of the primary, secondary and tertiary sector output gap in inflation. Output gap of each of these three sectors provokes inflation where the contribution of tertiary sector output gap is found to be the maximum followed by the primary sector and the secondary sector output gap. The prominent role of the output gap and comparatively passive role of monetary factors does not necessarily imply a non-effective monetary policy but suggests that controlling inflation only through the monetary management may not be effective.

This empirical analysis strives to properly investigate the potential consequences of the foreign exchange rate and money supply on retail food inflation. It also endeavours to explore the commodity-wise food inflation volatility in Indian outlook. The successful outcome of the ARDL technique sufficiently reveals that in the short run, money supply and foreign exchange rate have a direct impact on food inflation. While on the other hand, in the long run, foreign exchange rate produces a negative impact on food prices. The outcome of causality examination demonstrates that there is no causality running from money supply towards the food inflation, while on the other hand, unidirectional causality exists from the foreign exchange rate toward food inflation in India. Moreover, the result of the volatility analysis reveals that commodities like vegetables, pulses, condiment, fruits, and tea have double-digit inflation with high volatility. While on the other hand, essential commodities such as egg, meat, fish, cereal and milk seem less volatile. The disintegration result amply demonstrates that grains, drain, egg, meat, and fish have a tremendous contribution to the food prices expansion.

To test the existence of impossibility trinity constraint in the Indian context, we build three impossible trinity indices, viz., capital account openness, monetary independence and exchange rate stability using data for the period 1991-2018. We find the evidence on the existence of the trilemma where the constraint increases with rise in capital account openness. We also find that monetary independence comes at the cost of exchange rate stability. Our results on the implications of movements in trilemma in the presence of international reserves on inflation suggest that exchange rate stability has been effective in reducing inflation in India and remains a dominant policy choice. A rise in the flows of international reserves, however, could increase inflation, albeit the effect is negligible, reflecting inadequate sterilisation operations by the central bank.

Inflation in India has been a major cause for concern in the recent past (2008–2012). This study examines the Indian wholesale price index inflation from 1951 to 2012 using P-star (or P*) models after accounting for the nonlinearities in the data by establishing the presence of a nonlinear long-run equilibrium. The paper establishes the presence of a threshold vector error correction model (TVECM) between prices and their long-run equilibrium with three optimal regimes to explain the short-run and long-run dynamics based on an error correcting transition term. Based on these results, the study classifies the various regimes that Indian inflation goes through based on historical economic events. The P* models (price gap, output gap and velocity gap models) were implemented regime-wise. The price gap models (output gap and income velocity gap determine inflation) were found to be optimal in the first and second regimes and consistent with theory. The velocity gap model (which has monetarist foundations) was found to be optimal in the third regime.

Absence of inflation hedges and lack of inflation indexation in India make the society very sensitive to inflationary pressures. A potential source of such pressures that is often mentioned is the depreciation of the Indian rupee which has occurred over the last few years. This study computes the exchange rate pass-through into import prices of India at the aggregate level for the period 2003m1 to 2013m3 using both trade-weighted and bilateral USD exchange rates. The study also examines the asymmetry and non-linearity in the exchange rate pass-through at the aggregate level. The results suggest that there is more than complete exchange rate pass-through into Indian import prices in the short run and even higher pass-through in the long run, indicating the inertial effect of rising prices. There is also evidence of non-linearity in exchange rate pass-through, in terms of whether the rupee is appreciating or depreciating, as well as in terms of whether there are small or large changes in the rupee value.

Abseact:Main objective was to check the cointegration between inflation and import prices, interest rate, gross domestic product and money supply. Engle Granger cointegration (two step method) was applied to check the long run as well as short run relationship. ADF test was used to check the stationarity of variables. All the variables are stationary at first difference, so cointegration test was applied. Cointegration exists among inflation and import prices, interest rate, gross domestic product and money supply. There is long run relationship between inflation and independent variables including interest rate and gross domestic product. Import prices and money supply have no long run impact on inflation. There is short run relationship between inflation and interest rate and gross domestic product. No short run relationship is found between inflation and import prices and money supply.

The paper attempts to identify the determinants of inflation in India in a multivariate econometric framework using quarterly data from Q1: 1996–1997 to Q3: 2013–2014. The identified determinants of domestic inflation such as crude oil prices, output gap, fiscal policy and monetary policy, and their relation with inflation is studied in a structural vector auto regression (SVAR) model. Further, the temporal changes in inflation dynamics are analyzed using a time varying parameter SVAR model with stochastic volatility. It was found that inflation dynamics in India have changed over time with various determinants showing significant time variation in the recent years, particularly after the global financial crisis.

This paper provides a framework for analyzing different dimensions of Official Statistics based on the sentiments conveyed from various sources such as policy statements, expectation surveys, survey of professional forecasters, etc. This study for investigating the dynamics of inflation in India is based on the sentiments conveyed from Daily Newspaper, Household’s Inflation Expectation Survey, Survey of Professional Forecasters on Macroeconomic Indicators and Consumer Confidence Survey. The study uses applications such as Mathematica, etc. to apply different Machine Learning Models to learn the outcome of sentiments and provide a platform for determining the Inflation Trend. Further, an overview of Blockchain application for distributed and secure ML Models for Official Statistics is also discussed.

This paper examines the impact of fiscal policy initiatives on wholesale price index (WPI) based inflation in India. Total central government expenditure has been taken as the proxy for fiscal policy initiatives. The models used are VECM and ARDL-bound testing for estimating long run relationship. The results show that there is long run relationship between total central government expenditure and inflation in India. The IRF shows that if fiscal expenditure is given a positive shock of 100.0%, its cumulative impact on WPI in 5 years will be 14.0%.

Traditional concept of the Sacrifice Ratio measures the loss of potential output sustained by the society in the medium term to achieve reduction in the long-run inflation by 1% point. This concept is critically examined and generalized to include episodes increasing the long-run inflation rate to gain higher growth of output and employment and hence reduction in the poverty proportion in the medium term. Since the concept needs measurement through a shifting short-run equilibrium of dynamic aggregate demand and supply in terms of inflation rate and output attributable to monetary policy interventions, its estimation is challenging. There are two alternative approaches to estimate the ratio, the direct one and regression based. Both have their relative merits and demerits. The regression-based approach provides one unique average estimate of the Sacrifice Ratio for all episodes but allows holding other factors constant. The direct approach provides separate estimates by episodes but fails to hold other factors constant. The Sacrifice Ratio turns out to be in a narrow range of 1.8–2.1 for deliberate deflation and 2.8 for inflation in India. On the other hand, benefits of 1% point reduction in trend rate of inflation are at best 0.5% points increase in long-term growth of output that occurs after 4–5 years. This has implications on policy to disinflate.

This article investigates the impact of oil price volatility on six major emerging economies in Asia using time-series cross-section and time-series econometric techniques. To assess the robustness of the findings, we further implement such heterogeneous panel data estimation methods as Mean Group (MG), Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators to allow for cross-sectional dependence. The empirical results reveal that oil price volatility has a detrimental effect on these emerging economies. In the short run, oil price volatility influenced output growth in China and affected both GDP growth and inflation in India. In the Philippines, oil price volatility impacted on inflation, but in Indonesia, it impacted on both GDP growth and inflation before and after the Asian financial crisis. In Malaysia, oil price volatility impacted on GDP growth, although there is notably little feedback from the opposite side. For Thailand, oil price volatility influenced output growth prior to the Asian financial crisis, but the impact disappeared after the crisis. It appears that oil subsidization by the Thai Government via introduction of the oil fund played a significant role in improving the economic performance by lessening the adverse effects of oil price volatility on macroeconomic indicators.