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This paper aims to study, by means of an empirical approach, how monetary policy might affect the distribution of individual income.

After describing the channels through which monetary policy could impinge on income distribution, the authors carry out a panel analysis of 62 countries that control their monetary policy for the period 1996–2015.

Using two possible proxy variables for monetary policy (the monetary aggregate M3 and the real interest rates), the results reveal a significant positive relationship between real interest rates and income inequality measured through the market Gini coefficient and polarization ratios. The findings suggest that central bankers should be more aware of the redistributive effects of monetary policy.

It should be mentioned the major challenge of data limitation in the empirical investigation on the relationship between monetary policies and inequalities.

The empirical evidence presented in this paper supports the premise that central bankers should not ignore the unintended redistributive consequences of their actions. In this regard, it is worth noting that if, in addition to price stability, central banks are also responsible for financial stability; the rationale behind central bank independence needs to be reconsidered.

An outstanding feature of the paper is its sample size and the variety of countries included in the sample, which includes countries from all continents and with very different levels of economic development. Also, unlike papers based on forecasting modeling – e.g. Vector autoregression (VAR) or Structural vector autoregression (SVAR) models, the study follows an explanatory approach, including not only monetary variables, but also a series of regressors that may have a meaningful and significant impact on inequality, according to a wide literature.

The purpose of the paper is to address money demand instability and investigate the impact of economic uncertainty, stock market uncertainty and monetary uncertainty on money demand in India over the period 2003Q1–2019Q4.

The study checks the stationarity of the variables through standard unit root tests. Based on the mixed order of variables' integration, the authors adopt the autoregressive distributed lag (ARDL) model to confirm the cointegration and check the stability of the money demand function (MDF).

The findings confirm the presence of cointegration and reveal a well-specified MDF, which exhibits stable parameters. Besides the conventional variables, all forms of uncertainties emerge as the essential long-term determinants of money demand. Long-run findings show that people demand more money to avoid the future financial crunch amid high economic, monetary and stock market uncertainties.

The paper recommends, based on the findings, incorporating the monetary aggregates in the monetary policy framework as one of the essential information variables to control the fluctuation in the price level under the current flexible inflation targeting (FIT) regime.

The findings also add to the knowledge of economic agents in terms of the overall response of individuals to changes in different forms of uncertainties, thereby helping to formulate their portfolios more diligently.

The current work is the first of its kind in the Indian context. The incorporation of uncertainty measures in the MDF adds to the existing knowledge on money demand.

The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.

The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.

Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.

There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.

Having defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood.

Conceptual variables that are representative of liquidity will be used to formulate the predictions. The results of various machine learning models will be compared, leading to some reflections on the predictive value of the liquidity variables, with a view to defining their selection.

The predictive capacity of the model was also found to vary depending on the source of the liquidity, in so far as the data on liquidity within the private sector contributed more than the data on public sector liquidity to the prediction of economic fluctuations. International liquidity was seen as a more diffuse concept, and the standardization of its definition could be the focus of future studies. A benchmarking process was also performed when applying the state-of-the-art machine learning models.

Better understanding of these variables might help us toward a deeper understanding of the operation of financial markets. Liquidity, one of the key financial market variables, is neither well-defined nor standardized in the existing literature, which calls for further study. Hence, the novelty of an applied study employing modern data science techniques can provide a fresh perspective on financial markets.

因此,就了解經濟週期和經濟發展而言,流動資金是一個極其重要的概念。本研究擬在安全資產的價格預測方面取得進步。安全資產代表了經濟的實際情況,特別是美國的十年期國債。

流動資金的定義上面已說明了; 為進一步了解經濟波動,本研究擬對流動資金代表性變量的預測能力進行評估。

研究使用作為流動資金代表的概念變項去規劃預測。各機器學習模型的結果會作比較,這會帶來對流動資金變量的預測值的深思,而深思的目的是確定其選擇。

只要在私營部門內流動資金的數據比公營部門的流動資金數據、在預測經濟波動方面貢獻更大時,我們發現、模型的預測能力也會依賴流動資金的來源而存在差異。國際流動資金被視為一個晦澀的概念,而它的定義的標準化,或許應是未來學術研究的焦點。當應用最先進的機器學習模型時,標桿分析法的步驟也施行了。

若我們對有關的變量加深認識,我們就可更深入地理解金融市場的運作。流動資金,雖是金融市場中一個極其重要的變量,但在現存的學術文獻裏,不但沒有明確的定義,而且也沒有被標準化; 就此而言,未來的研究或許可在這方面作進一步的探討。因此,本研究為富有新穎思維的應用研究,研究使用了現代數據科學技術,這可為探討金融市場提供一個全新的視角。

This paper aims to assess the short- and long-run effects of the interaction between institutional quality and financial development (FD) on the competitiveness of the WAEMU economy over the period 2007–2018.

The methodology consisted of cross-referencing a synthetic indicator of FD with indicators of institutional quality and then estimating an auto regressive distributed lag model.

The results of the pooled mean group and dynamic fixed effect estimation show a positive and significant impact of this interaction on the competitiveness of the economy in the long run. In the short run, the results are quite similar to those in the long run for the direct effects but different for the crosses. Also, the analysis of country specificity shows that the results are similar to those in the short run since the interaction between FD and institutional quality (political stability and government effectiveness) negatively affects the competitiveness of Burkina Faso, Ivory Coast and Mali, and positively affects the competitiveness of Benin and Senegal.

These results suggest the need for effective policies to improve the quality of institutions to enhance the mobilization of financial resources through FD to ensure the competitiveness of economies. Improving the quality of the political and institutional environment is a prerequisite for economic competitiveness.

The paper is in line with the New Institutional Economics that developed in the 1970s. This referential framework is a heterogeneous body of work that encompasses works whose common point is the determination of the role of institutions in economic coordination. Unlike previous studies, which have focused on the contribution of the interaction between institutional quality variables and FD on economic growth, this paper analyzes the effects of this interaction on economic competitiveness. It, therefore, constitutes a contribution to this literature and aims primarily to fill this gap.

This paper empirically investigates the effect of economic policy uncertainty (EPU) on the UK money demand stability during the inter-war period (1920–1938). Both a narrow definition (M0) and a broad definition (M3) of money are investigated.

The empirical investigation is conducted by employing the autoregressive distributed lag (ARDL) bounds testing approach to cointegration.

Results presented indicate a stable demand for both definitions of money only when EPU is included as one of the determinants of demand function. The EPU imposes a negative effect on the demand for both definitions of money. The causality test results further indicate long- and short-term causality from the determinants (including EPU) to both forms of money demand.

Significant presence of the economic uncertainty weakens the effects of the monetary policy on the economy.

This is a historical economics paper. Given the turmoil and uncertainty associated with the inter-war period, an empirical investigation of UK money demand is an interesting exercise. This is the first such paper.

This study contributes to the pool of knowledge about the impact of monetary policy communication of central banks on financial instruments' prices and assets' value in emerging markets.

Empirical analysis is executed using the National Bank of Poland (NBP) announcements about its monetary policy covering the data from the broad financial market in its three main segments: stock market, foreign exchange market and bonds market. The reactions are measured relative to the changes in the NBP announcements and also with respect to investors' expectations. Autoregressive conditional heteroscedasticity (ARCH) models with dummy variables are used as the main methodological tool.

Bonds market and foreign exchange market are the most sensitive market segments, while interest rate and money supply are the most influential types of announcements. The changes of the revealed new macroeconomic figures had more impact on assets' prices movements than the deviations from their expectations. Moreover, greater diversity of the Monetary Policy Council (MPC) members' opinions on the voted motions, captured in the MPC voting reports, is associated with more cases of statistically significant NBP communication events.

The findings have direct relevance for fund managers, portfolio analysts, investors and also for financial market regulators.

The results provide novel evidence about how the emerging financial market responds to monetary policy announcements. They help understand the nature of the impact of public information on financial assets' valuation and on movements of their prices, analysed comprehensively in three market segments, in the emerging market environment.

Fiscal and monetary policies are essential to the development of a capital market. In this chapter, authors present how fiscal and monetary policy in Poland evolved and adjusted to economic challenges in 1998–2022. It is worth noticing that the Polish economy and financial market have been built from scratch after 45 years of socialism. Hence, it is scientifically interesting to study the relationship between fiscal and monetary policy, and capital market in a developing country, and in a relatively young economy.

Both – the macroeconomic policy mix and development of the capital market – are the subject of analysis how fiscal and monetary policy impacted the capital market. As so the main aim of the chapter is the assessment of the nexus and dependencies between fiscal and monetary policy and the capital market.

In the chapter, multiple linear regression was used for each dependent variable to discover which monetary and fiscal policy parameters significantly predicted selected variables describing the development of the capital market in Poland. Fiscal and monetary policy variables served as descriptors explaining capital market parameters in seven separate models.

Multiple regression models explain 77.3%–95.4% of the volatility of the capital market characteristics. The level of the central bank's reference rate is a variable that influences the capital market the most. In six out of seven models, the interest rate was a significant parameter. The development of the capital market was accompanied by a higher tax-to-GDP ratio. At the same time, a strong negative impact of the tax-to-GDP increase was noticed in domestic institutional investors' stock trading.

This paper analyzes the effects of the monetary stance on the media's favorable (or otherwise) attitude to the State Bank of Vietnam's (SBV) monetary policy using monthly data from 2011 to 2021. Monetary stance is a multivariate index based on the growth rates of money supply and domestic credit. A large set of articles published in five Vietnam daily newspapers are utilized to construct a view of the media's favorableness to the monetary policy.

This paper uses hand-collected data from 211 articles published in five newspapers from December 2011 to September 2021 in order to examine the relationship between the monetary stance and the media's favorableness to monetary policy. Following the studies of He and Pauwels (2008) and Xiong (2012), the authors constructed a multivariate stance index to capture most of the important changes in the SBV's monetary policy stance.

The study's main findings are that a change in monetary stance from easing to neutral/tightening, or from neutral to tightening, is greatly appreciated by the media. The study's findings are robust, especially in terms of alternative measures of the media's favorableness and monetary policy variables.

These findings have important policy implications for implementing SBV's monetary policy.

The main contribution of this paper is that the authors are the first to study the nexus of multivariate monetary stance and the media's favorableness to a central bank's non-inflation-targeting mandate. In particular, the study’s findings confirm that the SBV's multivariate monetary stance affects the media's favorableness, whereas the effect of inflation is statistically insignificant.

This study aims to explore the impact of monetary policy on bank lending rate with the moderating effects of financial sector development for eight Asian developing economics.

This study uses panel autoregressive distributed lag/pooled mean group estimation over the period ranging from 1980 to 2020.

The empirical results exhibit an inverse link between monetary policy measured by broad money supply on the bank lending rate, indicating that the increase in the money supply by the central bank lowers the demand for loans and thereby lowers the cost of loan. Moreover, financial sector development decreases the lending rate and thus lowers cost of loan. It is also noted that the interactive term of monetary policy by lending broad money supply and financial sector development showed a positive impact on the lending rate in selected Asian developing countries during the period under the study.

The outcomes have many relevant policy implications that stronger financial development sector contributes to the efficiency of monetary policy. Regulators and policymakers are therefore recommended to pursue greater financial sector development to lower the cost for fund searchers and to lower the cost of loans, money supply increase is suggested.

This study contributes to the extant literature on the factors affecting lending rate with the prime aims of monetary policy effectiveness. This study also included financial sector development with some other variables and an interactive term of monetary policy with financial development to have new insight impact of both on the lending rate in developing Asian economies.