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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.

This paper aims to contribute to the analysis concerning how inflation forecasts from different economic agents (professional forecasters and consumers) lead to varying levels of central bank credibility and how it affects the monetary policy interest rate and its expectations.

Based on the Brazilian economy data from June 2007 to May 2022, the authors provide evidence that is useful for search mechanisms that improve the conduct of monetary policy through the management of inflation expectations. The authors perform several ordinary least squares and generalized method of moments regressions inspired by the Taylor rule principle. In brief, the benchmark model considers that the monetary policy interest rate and its expectations respond to departures of inflation expectations to the target (a proxy for central bank credibility) and the level of economic activity.

The main result of the analysis is that inflation expectations from professional forecasters and consumers imply different perceptions of central bank credibility that affect the monetary policy interest rate and expectations for horizons until one year ahead.

The novelty that the authors bring from the analysis is that the authors calculate central bank credibility by taking into account the “public beliefs” of different economic agents. Furthermore, the authors analyze the effect of central bank credibility from professional forecasters and consumers on the monetary policy interest rate and its expectations.

The agricultural sector remains the backbone of several emerging economies, including Kenya, where it contributes 34% to its gross domestic product (GDP). However, access to financing for agricultural activities appears to be very low compared to developed economies. Following this, governments in a number of countries have sought to introduce banking sector regulations to facilitate increased funding to the agricultural sector. Taking motivation of the interest rate capping regulations by the Central Bank of Kenya (CBK) in 2016, this paper examined the effect of these interest rate ceiling regulations on agri-lending in Kenya.

The paper employs random effects technique to estimate a panel data of 26 commercial banks in Kenya from 2014 to 2018 using the ratio of loans to agricultural sector to gross loans and the natural logarithm of loans to agricultural sector as proxies for agri-lending. Bank size, equity, asset quality, liquidity, revenue concentration and bank concentration are employed as control variables.

The results of the panel regression estimations show that the introduction of the interest cap resulted in increases in the proportion and growth in agri-lending compared with the pre-interest cap period. In addition, large banks and highly capitalised banks were found to be associated with lower agri-lending, with differences in the effects across pre-cap and post-cap periods.

From a policy perspective, the findings highlight the effectiveness of interest rate capping in meeting this objective and supports the calls for strengthening cooperation between the government and key stakeholders in the financial sector. This will allow for the effective enforcement of policies by the regulatory powers in a manner that guarantees sound and dynamic financial systems, particularly within the agricultural sector.

As far as the authors are aware, this the first paper to examine the effect of the interest rate cap regulation on agri-lending in Kenya.

Interest rate derivatives (IRDs) are the essential components of financial risk management and are used across various industry sectors. The objective is to analyze the differences in approach to managing interest rate risks between the Indian corporates that execute IRDs and the ones that do not.

Interest rate fluctuations require Indian corporates to hedge their exposures in foreign currency interest rates. This is all the more true for mid-sized corporates because of their balance sheet exposures. Additionally, they may not have the resources to formulate risk management policies. This paper analyzes data collected from financial statements of a diverse set of companies that use IRD and helps in formulating such a strategy.

The results indicate significant differences for some of the parameters like information asymmetry and agency cost between users and non-users of IRDs. The study further suggests causality between users of derivatives and parameters like size, growth and debt.

The study compares users and non-users of IRDs, thereby identifying factors unique to users of IRDs. It also studies causality relations which explain the motivation to do IRDs. Thus, it enables risk managers to use this as a reference point to decide on their strategies.

While there are multiple studies across geographies and sectors including commercial banks in India on the usage of interest rate swaps, this study focuses on Indian mid-tier corporates. Furthermore, the study distinguishes between users and non-users based on financial parameters, which in turn would provide a framework for decision-hedging strategies.

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 paper aims to achieve two goals: first, to evaluate the existing interest-free monetary policy tools in the major Islamic financial hubs of Malaysia, Pakistan and Bahrain and; second, to suggest how monetary policy tools in Turkey can be used in other countries.

This study follows a qualitative research method based on literature review, comparison, evaluation and design.

The policy rate cannot be used due to Shariah concerns. The reserve requirement depends on qard, and the reserves should be kept separately in the central bank. In terms of ijarah sukuk, Shariah concerns should be taken into account and a new structure, as displayed in Figure 3, should be followed. Government investment certificates can be used as an interest-free monetary policy tool. A genuine mudarabah interbank investments can also be used. Wadiah acceptance with no habitual gift can be used as well, and Tawarruq and central bank notes are not preferable due to Shariah concerns as well. Having said that, a Turkey-based tawarruq platform can be structured for others to use instead of applying to London.

This paper’s unique suggestion is to develop an interbank taqaruz market and a taqaruz method with the central bank. It is also unique for Turkey in the subject.

This paper studies the dynamic effects of selected macroeconomic factors on the performance of the housing market in Kenya using Autoregressive Distributed Lag (ARDL) Models. This study aims to explain the dynamic effects of the macroeconomic factors on the three indicators of the housing market performance: housing prices growth, sales index and rent index.

This study used ARDL Models on time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited.

The results indicate that household income, gross domestic product (GDP), inflation rates and exchange rates have both short-run and long-run effects on housing prices while interest rates, diaspora remittance, construction output and urban population have no significant effects on housing prices both in the short and long run. However, only household income, interest rates, private capital inflows and exchange rates have a significant effect on housing sales both in the short and long run. Furthermore, household income, GDP, interest rates and exchange rates significantly affect housing rental growth in the short and long run. The findings are key for policymaking, especially at the appraisal stages of real estate investments by the developers.

The authors recommend the use of both the traditional hedonic models in conjunction with the dynamic models during real estate project appraisals as this would ensure that developers only invest in the right projects in the right economic situations.

The imbalance between housing demand and supply has prompted an investigation into the role of macroeconomic variables on the housing market in Kenya. Although the effects of the variables have been documented, there is a need to document the short-run and long-term effects of the factors to precisely understand the behavior of the housing market as a way of shielding developers from economic losses.

The authors empirically aim to study the implications of uncertainty generated by oil price volatility on some key macroeconomic variables, including production, exchange rates and interest rates, of both oil-exporting and oil-importing countries. Using a block exogeneity structural Vector Auto Regression (VAR) model that mutes the effects of domestic variables on global factors and that is suitable for small open economies because of significant differences in the responses of domestic production in oil-importing countries will most likely decrease through reducing planning horizons, postponing investment projects and relocating resources more inefficiently.

The authors integrated into the structural vector autoregressive (SVAR) model the block exogeneity feature since all the countries in this study are small open economies that cannot influence the global economic variables. The block exogeneity feature imposes the restriction that the domestic variables have neither a contemporaneous nor a lagged impact on the global variables. This model has eight variables: oil price volatility, world demand and federal funds rate as the global variables; and domestic production, monetary aggregate, inflation rate, exchange rate and interest rate as domestic variables. The authors assemble the data for 12 developing countries for which the necessary data for the analysis are available: six oil exporting countries (Russia, Saudi Arabia, Iran, Kazakhstan, Mexico and Colombia) and six oil importing countries (Turkey, India, Philippines, Poland, South Africa and Indonesia).

The results point out significant differences in the responses of macroeconomic variables to oil price volatility shocks between oil-exporting and oil-importing countries. Furthermore, the local currencies of these countries depreciate due to concerns about possible current account worsening. In response to the shock, domestic interest rates are reduced so as to alleviate the negative exposure of the shock on domestic economic activity. While domestic production in some oil-exporting countries (i.e. Russia, Saudi Arabia and Iran) increases during oil price uncertainty; in some other countries (i.e. Mexico, Kazakhstan and Colombia), domestic production decreases.

Several components of the study contribute to its novelty. One of them is the period under consideration. The time frame that encompasses the most significant geopolitical and financial events, such as the Middle East Spring and the global financial crisis of 2007–2008. The research was conducted using the block-exogeneity SVAR model, which includes 12 oil exporting and importing developing countries. With this model, the global dynamics, particularly the energy market, that these nations may influence and are influenced by, i.e. global and nonglobal factors can be constrained. This makes it easy to determine the various effects prices have on macroeconomic variables.

1. Oil prices and volatility still matter to the global economy

2. Monetary and fiscal policy interventions in response to oil price volatility create uncertainty and impede investment activity

3. The response of macroeconomic variables to volatility shocks in oil prices varies across oil importers and exporters

4. Interest rates help stabilize production in oil-importing economies that have well-functioning financial markets

Oil prices and volatility still matter to the global economy

Monetary and fiscal policy interventions in response to oil price volatility create uncertainty and impede investment activity

The response of macroeconomic variables to volatility shocks in oil prices varies across oil importers and exporters

Interest rates help stabilize production in oil-importing economies that have well-functioning financial markets

The idea of this study is to provide a solid Financial Condition Index (FCI) that allows the monetary transmission policy to be monitored in a country which in recent decades has suffered from major financial and monetary crises.

The authors construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime. Using monthly data from 1995 to 2017, the authors estimate FCIs with two different methodologies and build the index by taking into account the mechanism of transmission of monetary policy and incorporating the most relevant financial variables.

This study’s results show that, likewise for developing countries as Mexico, an FCI could be a useful tool for managing monetary policy in reducing macroeconomic fluctuations.

Apart from building a predictor of possible financial stress, the authors construct an FCI for a central bank that pursues inflation targeting and to analyse the role of financial asset prices in formulating monetary policy.

1. We construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime.

2. The FCIs are based on (1) a vector autoregression model (VAR); (2) an autoregressive distributed lag model (ARDL) and (3) a factor-augmented vector autoregression model (FAVAR).

3. FCI could become a new target for monetary policy within a hybrid inflation-targeting framework.

4. FCI could be a good tool for managing monetary policy in developing countries with a low-inflation environment.

We construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime.

The FCIs are based on (1) a vector autoregression model (VAR); (2) an autoregressive distributed lag model (ARDL) and (3) a factor-augmented vector autoregression model (FAVAR).

FCI could become a new target for monetary policy within a hybrid inflation-targeting framework.

FCI could be a good tool for managing monetary policy in developing countries with a low-inflation environment.

Credit is an essential element in the production process in agriculture. There are two sources from which farm households can access credit: institutional sources and non-institutional or informal sources of credit. The informal sources of credit, such as moneylenders, charge exorbitant rates of interest, which further puts a financial burden on the farmers. Hence, to increase the flow of credit from institutional sources, a policy known as the interest subvention scheme (ISS) was introduced in the year 2006. This paper aims to find the effect of the ISS on the behaviour of farm households.

The author has used difference-in-difference analysis for estimation. In the analysis, the author has taken Madhya Pradesh as the treatment state and Andhra Pradesh as the controlled state. The author has used the Village Dynamics in South Asia (VDSA) dataset of ICRISAT for analysis. The author has used data from 2009 to 2014 for the two states.

The author has found that the difference between the average interest rate of Andhra Pradesh and Madhya Pradesh is significant for both pre-treatment and post-treatment periods and this gap has increased after the intervention period. The results suggest that the share of informal sector borrowings has reduced in the treatment group (Madhya Pradesh) as compared to the control group (Andhra Pradesh) in the post-treatment period.

This paper is particularly important because of the dearth of literature on the impact of this scheme in India and may shed light on the much-needed policy implications of this particular policy.