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The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

We aim to conduct a bibliometric analysis that explores and maps quantitative data of the emerging field of central bank digital currencies in science and its implications in practice. We seek to clarify the underlying research structures and streams of the new phenomena, and our motivation is the rising number of pilots between governments seeking to implement different types of central bank digital currency.

We designed the unique set of keywords to explore ongoing projects on central bank digital currencies and the evolution of scientific thought on the topic. We conducted a descriptive analysis and an evaluating bibliometric analysis on the timeline from 2018 to April 18, 2023 and investigated 76 articles in the Web of Science database and 152 articles in the Scopus database using VOSviewer.

We highlight three main directions of discourse on central bank digital currencies in economics using authors keyword analysis, that are: (1) cash, (2) monetary policy and (3) financial stability. We conducted a map-based text analysis of the abstracts and identified the following main streams of discussion in the field: (1) policy-related research on financial systems, (2) a comprehensive review of the design and features of central bank digital currencies and (3) research on the impact of central bank digital currencies on the banking system.

The unique set of keywords allows us to continue the discourse on central bank digital currencies including implications of ongoing governmental projects on the topic and provide directions for future research. We brought the focus on the impact of central bank digital currencies on the banking sector and the new possible order for cash, deposits and payments.

This paper aims to test the hedging ability of housing investment against inflation in Japan and the USA during the period 2000–2020.

This study applies the deep learning method and The exponential general autoregressive conditional heteroskedasticity in mean (1, 1) model with breaks.

Within the asymmetric framework, it is found that housing returns (HR) can hedge against inflation in both these markets, which mentions that when investing in the housing market in Japan and the USA, investors are compensated for bearing from inflation. This result is consistent with Fisher’s hypothesis. Especially, the empirical results show that the risk-return tradeoff is available in Japan’s housing market and not available in the US housing market. Any signal of a high inflation rate – referred to as “bad news” – may cause a drop in HR in Japan and a raise in the USA.

To the best of the author’s knowledge, this is one of the first studies using the deep learning method (long short-term memory model) to estimate the expected/unexpected inflation rates.

Brazil uses the dollar as a vehicle currency to invoice its exports. This fact produces a tendency toward equalizing the prices of products in dollars in the international market and reducing the ability of firms to practice pricing-to-market (PTM). This study aims to evaluate the hypothesis by estimating error correction models in panel data, obtaining estimates of PTM for 25 manufacturing products exported by Brazil between 2010 and 2020.

This study uses the correlated common effect estimator proposed by Pesaran (2006) and Chudik and Pesaran (2015b) to estimate the PTM coefficients.

Results of this study indicate that exporters practice local-currency pricing stability for dollar prices. This study obtains that Brazilian exporters tend to stabilize their dollar price for exports, reducing heterogeneity between destination markets. The results are in agreement with the hypothesis of the prevalence of the coalescing effect of Goldberg and Tille (2008) and lower sensitivity of the markup adjustment to the specific market, as pointed out by Corsetti et al. (2018). The pricing of Brazilian exports in dollars reflects a profit maximization strategy that considers an international price system based on global demand for products.

In addition to analyzing the dollar role in the pricing of Brazilian exports through the triangular decomposition, this study also shows the importance of examining the cross-section dependence of errors, considering the heterogeneous cointegration in export pricing models and producing PTM estimates for short-term and long-term.

Besides the extensive research on managerial efficiency in the financial sector worldwide, emerging economies in Europe remain untapped. This research scrutinises the impact of managerial performance and competitive structures on their financial industry growth in terms of services they offer and ability to liquefy stock in capital markets.

This study contains data from selected emerging European countries' during the period of 2010–2020. This study uses data from the Heritage Foundation's Index of Economic Freedom to control for firm-level indicators. The fixed-effects (FE) method was used to explore the nexus between financial sector growth and management performance as well as competitive firm structure.

The findings provide evidence of the existing impact of firm indicators on the financial sector's growth. Two-step system the generalized method of moments (GMM) estimations are used for the robustness check of the authors' model. Whilst on a scavenger hunt through existing literature, the authors realise that there is an overwhelming lack of enthusiasm in this field.

With the intention of better assessment, the authors use regulatory contextual variables to look for any possible impacts and surprisingly discover a pattern in the financial growth nexus.

The purpose of this study is twofold. First, to estimate an optimal inflation rate for Ghana and second, to investigate factors that account for the differences between observed and target inflation.

The paper explored the questions within two econometric frameworks, the Autoregressive Distributed Lag (ARDL) and Threshold Regression Models using data spanning the period 1965–2019.

The study estimated a range of 5–7% optimal inflation for Ghana. While this confirms the single-digit inflation targeting by the Bank of Ghana, the range is lower than the central bank's band of 6–10%. The combined behaviours of the central bank, banks and external outlook influence inflation target misses.

The study urges the central bank to continue pursuing its single-digit inflation targeting. However, it implies that there is still room for the Bank to further lower the current inflation band to achieve an optimal outcome on growth and welfare. Again, the Bank should commit to increased transparency and accountability to enhance its credibility in attaining the targeted inflation.

The study is one of the first attempts in Africa in Ghana to estimate an optimal inflation target and investigate the underlying factors for deviation from the targets.

This paper aims to examine the interaction effect of regulations (monetary and macro-prudential) in explaining the possible non-linear effect of bank risk exposures (credit risk and insolvency risk) on banking stability in Africa.

The study uses a two-step system generalized method of moments (GMM) estimator for a data set of banks across 54 African countries over the period 2006–2020.

The authors find that the relationships between bank credit risk–bank stability and bank insolvency risk–bank stability are non-linear and characterized by the presence of optimal thresholds, which are 5.3456 for credit risk and 2.3643 for insolvency. Contrary to their positive effects below these optimal thresholds, credit risk and insolvency risk become negatively linked to bank stability in Africa. The authors find that macro-prudential action and monetary policy both have a positive and significant relationship with bank stability. The authors provide evidence to support that the marginal effect of excessive credit risk and insolvency risk on bank stability is reduced when interacted with monetary and macro-prudential regulations, and the impact is significant in strong institutional environment.

Future research should extend data to include developing and emerging economies in the world. Also, policymakers, researchers and practitioners should consider different regulatory and institutional frameworks in explaining the relationship between the thresholds of bank risk exposures and bank stability in the world.

Regulatory authorities should have to deeply reform their financial systems, develop risk-based regulatory framework and effective supervision mechanism relating to appropriate techniques that maintain an optimal and desired level of bank risks and risk-taking behaviours required to ensure a stable banking system.

To the best of the authors’ knowledge, this is the first study to examine how different regulatory frameworks shape the non-linear impact of bank risk exposures on bank stability in Africa.

The study examines how the liquid assets holdings among non-financial Indian firms vary due to tightening monetary policy and increasing macroeconomic uncertainty.

The authors analyze 5,640 firms for the period 2011–2021. The authors first estimate India’s monetary policy shocks by decomposing the exogenous shocks from the systematic component of monetary policy changes. The authors then examine the effects of the estimated monetary policy shocks and a range of macroeconomic and policy uncertainty indicators on companies’ cash and bank balances to asset ratios using two-step system generalized method of moments (GMM) estimators.

The authors find that monetary policy shocks cause the cross-sectional variances for the firms’ liquidity holdings to increase. In anticipation of macroeconomic volatility, companies respond to these shocks after taking into account all the firm-level information to minimize the opportunity costs of holding extra cash or too few cash balances that can hamper firms’ operations. Furthermore, compared to other shocks, the contribution of inflation-induced shocks is predicted to be the largest in the cross-sectional deviation of the firm’s cash holdings. The authors also find that low-growth, older and financially constrained firms observe lesser heterogeneity in their cash holdings as they tend to hold cash as a precautionary buffer.

The authors’ approach to the analysis is unique in many ways. To address potential transmission bias, the authors use nowcasts and forecasts of real gross domestic product (GDP) growth and inflation to generate a series of exogenous monetary policy shocks for identifying unanticipated changes in short-term interest rates. Subsequently, the authors estimate how these shocks affect the cross-sectional deviation of liquid assets. For estimating the effects of macroeconomic uncertainty on corporate cash demand, the authors utilize a range of proxies for uncertainty. Unlike previous attempts, the authors offer evidence for a developing and fast-emerging economy.

The purpose of this research is to examine the impact of alterations in the path of monetary policy rates on inflation via the supply side of an emerging economy.

The study employed semi-annual data covering the period 2007S1 to 2020S2 on the inflation rate, the combined outputs of industry and agriculture, the lending rate, and the monetary policy rate. The vector autoregression model was estimated and counterfactual simulation exercises were conducted.

The study revealed that a move from a higher to a lower monetary policy rate regime resulted in a shift in inflation from a higher to a lower regime. In particular, a 200-basis point reduction in the monetary policy rate over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

The study has a limitation due to the unavailability of a long-span dataset on all relevant variables. As a result, it is important to exercise caution when interpreting the study's findings. A potential area for further research is to explore how changes in interest rates impact inflation in the real economy by utilising other multiple-variable time series techniques.

It is the opinion of the authors that for inflation in Ghana to move to a lower regime, conscious efforts should be made by the monetary authorities to gradually move from a regime of a high monetary policy rate to a lower one.

In particular, a 200-basis point reduction in the MPR over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

This study enhances the authors' knowledge of how monetary policy can affect inflation in developing countries through the supply-side channel.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.