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In this paper, we study the effect of global energy and food inflation on household inflation expectations during the period 1988M01–2020M03 for a set of European economies.

We use multifractal de-trended cross-correlation analysis to estimate the non-linear and time-varying cross-correlation. We provide additional robustness tests using the Autoregressive-Distributed Lag method.

We find that household inflation expectations, global energy inflation and global food inflation are all multifractal. We also find that the household inflation expectations, global energy inflation and global food inflation are positively correlated (i.e., they are persistent). However, household inflation expectations respond more when the volatility of the global energy inflation is lower than when the volatility is higher. The correlation between household inflation expectations and global food inflation does not depend on the level of volatility.

First, paying attention to the global commodity inflation might help anchor inflation expectations better. It is so because Central Bank's efficacy in achieving price stability may be weakened if there is a relationship between commodity inflation and inflation expectation. This task would become even more difficult in the average inflation targeting regime than inflation targeting regime if actual inflation is persistently different from the target inflation. Second, our results also emphasize the importance of effective strategy for communicating to households about actual inflation, inflation target and keep them updated about how monetary policy functions.

We contribute to the literature by estimating the cross-correlation between household inflation expectations with the global commodity inflation, conditional to the volatility of the commodity inflation under consideration.

The authors model heterogeneity of inflation expectations across Indian households using the Inflation Expectations Survey of Households data set. Using Carroll-type epidemiological models and pooled cross sectional analyses, the authors find that women, homemakers, older people and Tier 2 and 3 city dwellers tend to have higher inflation expectations compared to their counterparts. In the epidemiological model-based analysis, these very cohorts display higher speed of adjustment to news. Overall higher relative adjustment speeds point to the significance of central bank communications.

The author analyzes households' inflation expectations data for India, collected quarterly by the RBI for more than a decade. The contribution of this paper lies in two folds. First, this study examines the relationship between relatively recent inflation expectations survey of households (IESH) and the actual inflation for India. Secondly, the author employs a structural VAR with the time period 2006 Q2 to 2020 Q2 on inflation expectation survey data of India. A short-term non-recursive restriction is imposed in the model in order to capture the simultaneous co-dependence causal effect of inflation expectation and realized inflation.

This paper studies the dynamic behavior of inflation expectations survey data in two folds. First, the author analyzes the time series property of the survey data. The author begins with testing the stationarity property of the series, followed by the casual relationship between the expected and actual inflation. The author further examines the short-run and long-run behavior of the IESH with actual inflation. Employing autoregressive distributed lag and Johansen co-integration, the author tested if a long-run relationship exists between the variables. In the second approach, the author investigates the determinants of inflation expectations by employing a non-recursive SVAR model.

The preliminary explanatory test reveals that inflation expectation is a policy variable and should be used in monetary policy as an instrument variable. The model identifies the price puzzle for India. The author finds that the response of inflation to a monetary policy shock is neutral. The results also indicate that the expectations of the general public are self-fulfilling.

IESH has only commenced from September 2005, hence is relatively new as compared to other survey in developed countries. Being a new data set so far, the author could not locate any study devoted in analyzing the behavior of the data with other macroeconomic variables.

The study intends to evaluate the impact of inflation expectation on the performance of listed commercial banks in India during 2005–2021. Inflation expectation is considered as a direct policy tool by the policymakers for stability of the economy. The study explores how inflation expectation affects the performance indicators of the Indian banking industry while controlling for a wide range of bank-specific factors.

The study applies the generalized method of moments (GMM) on a panel sample of 27 listed bank to analyse the impact of inflation expectation on banking sector performance. The data on inflation expectation are obtained from the household inflation expectation survey introduced in India by the Reserve Bank of India in 2005. Return on assets (ROA), return on equity (ROE) and Tobin's Q have been considered as the banking performance indicators in this study.

Empirical results exhibit that inflation expectation is instrumental in deciding the banking sector's performance. Inflation expectation has been found to have a significant and positive impact on accounting-based measures of banking performance. At the same time, it shows negative impact on the marketing-based measure.

The study gives a clear picture about how inflation expectation affects the banking performance and the monetary policy of the country. The study provides crucial insights to develop strategic decisions for the Indian banking sector. The adoption of proper macroeconomic policies, taking into account inflation expectation levels, is instrumental in enhancing bank's performance and in achieving economic growth.

This study contributes to the growing body of literature on the impact of inflationary conditions on banking performance. The originality lies in capturing the role of inflation expectation solely in determining banking sector performance.

The Inflation Expectations Survey of Households, conducted by the Reserve Bank of India (RBI), indicates that there is considerable disparity in inflation expectations across cities in India. The purpose of this paper is to investigate why different cities exhibit heterogeneous inflation expectations despite coming under a central monetary policy umbrella.

First, the correspondence between city-level inflation expectations and city-specific economic characteristics is mapped. Second, how the disagreement in inflation expectations across cities, measured by dispersion, behaves over the business cycle is investigated. Finally, using seemingly unrelated regression technique, the economic factors that play a role in explaining inflation expectations heterogeneity across cities are estimated.

Cities with higher economic activity and cost of living have higher inflation expectations. Disagreement across cities regarding inflation expectations rise with an increase in output gap and inflation. Information friction plays an important role in explaining the disparity in inflation expectations across cities, and the effects of macro-level factors vary across cities, thereby accentuating expectations dispersion.

Monetary policy-related communication by the RBI (toward the general public) should increase in order to address information friction, which, in turn, would temper down the extent of inflation expectations heterogeneity across cities in India.

This is a novel application of the data from the monetary policy perspective. Heterogeneity in inflation expectations across cities or regions is an unexplored area. The use of nightlights as a proxy for city-level economic activity in India (in absence of data on city-level income) is another original contribution.

Inflation expectations are an important part of the transmission mechanism of the inflation targeting regime. As such, central bankers must study the inflation expectations of economic agents to anchor them close to the level of the inflation target. However, economic agents are affected by the past and current macroeconomic situation when they form their expectations concerning future inflation. Using survey data on inflation expectations in Czechia, we investigate the macroeconomic determinants of Czech analysts' and managers' inflation expectations. We find that both actual and past inflation have a substantial impact on inflation expectations of the agents surveyed. We also identify backward-looking behaviour among these agents: persistence in inflation expectations of up to two quarters was detected. Moreover, financial analysts formed inflation expectations more in line with economic theory, while company managers evinced expectations similar to those of consumers.

Sufficiently persistent rise in nominal interest increases inflation rate in short-run. This short-run comovement of nominal interest rate and inflation rate is known as Neo-Fisherianism. This chapter proposes a policy based on Neo-Fisherianism to escape Zero Lower Bound (ZLB) using a textbook Forward Looking New Keynesian Model. I have shown that proposed policy with properly chosen inflation target and persistence can stimulate economy and escape ZLB by raising nominal interest rate. I have also shown that the proposed policy is robust to varying degrees of price stickiness.

This paper presents an integrated overview of the empirical literature on the impact of all forms of unconventional monetary policy on macroeconomic variables and on markets.

This survey covers the findings concerning portfolio rebalancing, signaling, liquidity, bank lending and confidence channels.

The positive effect of QE announcements on stock and bond prices seems to be unified across studies. A contagion effect from US QE to other emerging markets is identified, while currency devaluation is present in most cases for the country that its central bank adopted such policies. Moreover, impacts of non-conventional practices on GDP, inflation and unemployment are examined. The studies presenting weak instead of strong positive effects on inflation are more, and these studies, also, present weak positive effects on GDP growth.

Based on the large body of research on non-conventional action taking, this is the first survey including effects of each country that adopted quantitative easing (QE) measures and that provides results from every methodology employed in order to estimate unconventional practices' impacts.

The chapter contains a methodology for formalized evaluation of the role of the Central Bank of the Russian Federation (Bank of Russia) in ensuring monetary and financial sustainability with the help of the monetary policy transmission mechanism and its inflation target regime. The significance of the research of the Bank of Russia operations to ensure financial sustainability is due to a number of circumstances: the uniqueness of the Bank of Russia that appeared only 27 years ago and experienced several devastating events related to the 1998 financial crisis, the global financial crisis of 2008–2009, and the stagnation of the Russian economy in 2014–2016, as well as high volatility of world prices for Russian commodity exports and the latest contra-Russian sanctions that significantly affected the volatility of the Russian ruble. Taking into account all the above, the issue of the Bank of Russia’s effective activities in the long run is aggravated by the fact that there are still more open questions than proven relationships of causes and effects regarding the potential of specific monetary policy instruments in the context of low-growth and high-volatility environment. The modeling of the Bank of Russia strategic and operational targets has been based on the parameters’ dependencies presented by the money (credit) multiplier in the interpretation of G. Schinasi (2006) and on the instability of stable economy hypothesis of H. Minsky (2008). As a result, there have been established the marginal levels of definite indicators of the banking system performance that could allow the Bank of Russia to ensure financial sustainability in the low-growth and high-volatility environment.

This paper aims to explain real exchange rate fluctuations by means of a model including both standard fundamentals and two alternative measures of inflation expectations for five inflation targeting countries (the UK, Canada, Australia, New Zealand and Sweden) over the period January 1993–July 2019.

Both a benchmark linear autoregressive distributed lag (ARDL) model and a nonlinear autoregressive distributed lag (NARDL) specification are considered.

The results suggest that the nonlinear framework is more appropriate to capture the behaviour of real exchange rates given the presence of asymmetries both in the long and short run. In particular, the speed of adjustment towards the purchasing power parity (PPP) implied long-run equilibrium is three times faster in a nonlinear framework, which provides much stronger evidence in support of PPP. Moreover, inflation expectations play an important role, with survey-based ones having a more sizable effect than market-based ones.

The focus on linearities and the estimation of a NARDL model, which is shown to outperform the linear ARDL model both within sample and out of sample, is an important contribution to the existing literature which has rarely applied this type of framework; the choice of an appropriate econometric method also makes the policy implications of the analysis more reliable; in particular, monetary authorities should aim to achieve a high degree of credibility to manage them and thus currency fluctuations effectively; the inflation targeting framework might be especially appropriate for this purpose.