Interest Rate Research Articles

While the opening of the bond market provides strong support for high-level financial opening, it also accelerates the accumulation of systemic financial risks, thereby affecting the high-quality development of China’s finance. Based on data from 2003 to 2024, this paper measures China’s bond market opening, monetary policy, and systemic financial risks, and employs a TVP-SV-VAR model to investigate the time-varying relationships among bond market opening, monetary policy, and systemic financial risks. The findings are as follows: (1) The impact of bond market opening on China’s systemic financial risks exhibits time-varying characteristics; (2) Contractionary monetary policy helps curb systemic financial risks, but this effect marginally diminishes when facing external structural shocks; (3) The improvement of interest rate transmission mechanisms and the transition toward price-based monetary policy can significantly enhance the sustainability of monetary policy’s regulatory role in systemic financial risks; (4) There exists a significant linkage effect between bond market opening and monetary policy, but this effect is subject to time-varying influences from the progress of domestic institutional reforms and cross-border capital anomalies.

The study is to understand the impact of motivation and job satisfaction on employee performance of Central Bank of Nigeria. To achieve the objectives set, primary and secondary sources data were used. Primary data was collected both from managerial and non-managerial employees of the Bank. The total population of the Bank branch is 200 from which 120 samples was taken using Convenience sampling technique. Much of the data was collected from the managerial category since this category performs the core jobs of the Bank which is to conduct monetary policy by managing the money supply, setting interest rates, and overseeing the banking system to maintain financial stability within a country. Correlation technique was employed to find out the relationship between two variables. Regression technique also was used to find out to which extent one variable affect the other using coefficient results. Correlation results for salary is 0.589, Transport benefits 0.421, medical benefits 0.395, extra duty allowance 0.421, carrier achievement 0.562, promotion benefits 0.672 and correlation for recognition is 0.407 which reveal existence of positive relationship between motivation and employees’ performance and therefore implying that the increase in motivation will lead to increase in employees’ performance. This situation insists on increasing attention to employee motivation practice in order to improve employee performance. The findings suggest enhancement of current motivation package by incorporating both intrinsic such as promotion, recognition, support for carrier achievement and extrinsic motivation factors such as salary, extra duty allowance, transport allowance, medical benefits will help optimum utilization of human resources as well as increasing employees’ performance. Furthermore there is pressing need to develop organisation motivation policy that will help the Central Bank Of Nigeria, Awka Branch management properly in handling motivation function.

ABSTRACT Financial inclusion can play an important role in reducing poverty and improving people's living standards in developing countries. Microfinance has significantly contributed to financial inclusion in Cambodia, but issues like the high debt burden among borrowers, especially those with inadequate financial literacy, have emerged. Borrowers with inadequate financial literacy often underestimate loan repayments and borrow at high interest rates for consumption and other unproductive uses. Understanding the level of financial literacy and the factors that influence it among microfinance borrowers in Cambodia is important for policy making. Using data and information from a household survey in 2021, our study examines the financial literacy landscape among microfinance borrowers in Cambodia and explores the factors influencing their financial literacy levels, focusing on personal and household characteristics. The findings provide insights for enhancing financial literacy and financial inclusion in Cambodia. From our analysis, we confirm (1) the importance of financial literacy in reducing access to informal finance, (2) a positive correlation between years of general education and financial literacy, (3) an association between poor households and lower financial literacy, and (4) a positive relationship between higher social capital (the social network within a community) and higher financial literacy.

In Zambia, microfinance institutions play a critical role in providing capital financing for Small and Medium Enterprises (SMEs). Despite microfinance’s contribution to SMEs’ capital financing, the impact is not evident because SMEs have been impended by high interest rates, collateral requirements, and other factors. This study assessed the effectiveness of microfinance capital financing on working capital, operating costs, and profitability of SMEs in Lusaka District, Zambia. A mixed-method approach was employed, combining qualitative and quantitative methods. Primary data were collected and analyzed using Megastat. The findings reveal a significant positive relationship between microfinance and SME's working capital growth, with a correlation coefficient (r = 0.534) and R-squared value (0.286). The significant test (F-statistics = 23.18, p-value = 0.00) confirms a statistically significant relationship. The study also finds a notable effect of microfinance on SME operating costs, indicated by the chi-square test (χ² = 32.79, df = 16, p = 0.0079). Regression analysis reveals a significant positive relationship between microfinance and operating costs, with a coefficient (0.4208, p = 0.0032). Furthermore, the study shows that microfinance capital has led to improved profitability for SMEs, with a mean response of 4.300 and a p-value of 0.0188. The findings also highlight the challenges faced by SMEs, including high interest rates (76.7%) and emotional and organizational strain (55%). The study recommends flexible disbursement schedules, sector-responsive repayment models, and tiered interest frameworks to enhance the effectiveness of microfinance. By integrating statistical testing with stakeholder perspectives, the research positions microfinance as a strategic instrument for SME resilience, growth, and inclusive economic development in Zambia.

ABSTRACT This study examines the complex relationships between macroeconomic policies and environmental pollution in Mediterranean countries through the lens of quantile regression analysis. Drawing on panel data from 19 Mediterranean nations spanning from 1990 to 2024, we investigate how fiscal, monetary, trade, and exchange rate policies affect CO 2 emissions across different points in the pollution distribution. Our findings reveal significant heterogeneity in policy effects, with explanatory power increasing substantially from lower to higher emission quantiles. Fiscal constraints, represented by public debt levels, demonstrate increasingly positive associations with pollution as emission levels rise. Monetary policy instruments show varying effects, with interest rates positively associated with emissions particularly among high polluters, while credit expansion exhibits a transition from negative to positive effects across the distribution. Trade openness consistently shows negative relationships with emissions, contradicting the pollution haven hypothesis for this region. Exchange rate appreciation is associated with higher emissions, with effects strengthening at upper quantiles. To address potential endogeneity concerns, we employ a two‐stage quantile regression approach, which confirms these patterns while highlighting the critical roles of fossil fuel consumption and renewable energy in determining emission outcomes. The results underscore the importance of integrated policy approaches that account for differential effects across pollution levels and emphasize the need to incorporate environmental considerations into core macroeconomic policy frameworks. These findings contribute to our understanding of the macroeconomic–environmental nexus and offer insights for designing more effective environmental governance systems in the Mediterranean region.

ABSTRACT This paper studies the effect of reporting regulation on private firms' bank credit and its economic consequences. I exploit the Spanish institutional setting, which provides a unique combination of confidential loan data and regulatory features that generate quasi‐exogenous variation in reporting regulation. Using a regression discontinuity design, I find that firms subject to incremental reporting regulation obtain more bank credit primarily through cash flow–based lending, term loans, and long‐term debt, without higher interest rates. These findings are explained by stronger banking competition and greater reliance on financial statement data. However, firms do not expand their net financial position, as bank credit substitutes for other liabilities, and exhibit weaker performance consistent with the costs of reporting regulation. This evidence from a different setting offers new insights into how reporting regulation influences credit contracting for private firms and strengthens the empirical basis for policy‐making.

The natural rate of interest through a hall of mirrors

Are higher interest rates a concern for financial stability in MENA?

Inequality’s ripple effect: Analyzing its influence on the natural interest rate and monetary policy in Germany, Japan, and the US

Physics-informed neural network for barrier option pricing in coupled financial quantitative system with varying interest rate and volatility

This work verifies the interactions between fiscal and monetary policies in Brazil, involving real GDP, the Interest index, Inflation index, real Exchange rate, and actual public debt, using empirical data from January 1998 to December 2018 to calibrate the model. In the analyses, we employ macrodynamic deterministic and stochastic models of differential equations to examine the interconnection of the endogenous variables and the stability of Brazilian economic policy. In the stochastic model, we introduced stochastic perturbations in the uncontrollable coefficients and additive random walks affecting the endogenous variables. Shocks imposed on the structured dynamic model showed that stochastic innovations propagate more strongly in the monetary variables: inflation, interest rates, and exchange rates. We have also established forecasts for endogenous variables from January 2019 to December 2026 and conducted backtest analyses using the empirical data observed for the endogenous variables from January 2019 to December 2023. The forecast estimations were demonstrated to be satisfactory.

This study explores the predictive power of the sentiment captured in the minutes of the Monetary Policy Council (MPC) meetings regarding the setting of the reference interest rate in Poland. It assesses its usefulness in forecasting the returns on financial markets. The sentiment is computed with the VADER analysis tool. The release of the MPC meeting minutes impacts stock and Treasury bond markets but appears to have negligible effect on the foreign exchange market. Adding the sentiment as a feature enhances the forecast accuracy of daily stock index returns and bond yield changes generated by the LSTM machine learning models.

In this study, we examine the patterns and causes of stock market integration of twelve emerging markets against the US market, for the period January 2005 to January 2020. We compare patterns of market integration for countries on a monthly basis using the time-varying correlation technique, namely, GARCH-dynamic conditional correlations (DCCs). In doing so, we suggest that opportunities in cross border investment vary by frequencies. We also divide daily data into subsamples and find that correlations were strongest during the global financial crisis (GFC) of 2007–09. The time varying bilateral correlations are found to be highly volatile. We also investigate the causes of identified correlations and find that the underlying economic and financial conditions (exchange rate volatility, interest rate spread, trade openness and capitalization market) have also been responsible for the higher correlations between these stock markets.

We build a small open economy overlapping-generations model (SOE-OLG) to understand changes in the natural rate of interest in New Zealand over the period 2000–2024. We consider six drivers of the natural rate of interest: the world natural rate of interest, population growth, productivity growth, government debt levels, old-age labour force participation and longevity. We find that declining productivity growth and a lower world natural rate of interest are important for explaining the reduction in the New Zealand natural rate of interest, only partially offset by higher population growth, and to a lesser degree by increasing old-age labour force participation. The role of changes in government debt levels and longevity have been modest, with the change in these drivers over our analysis period being relatively small. Our results are based on defining the natural rate of interest as the long-run equilibrium real interest rate. In the model, the domestic natural rate of interest is equal to the world natural rate of interest plus a premium. The size of this premium reflects the difference between domestic capital stock and domestic savings, which is the net foreign position.

Tutorial groups in higher education spark students’ interest and promote independent study. But does an interesting problem lead students to invest time in their studies? This study examined whether students’ interest in problems discussed in problem-based learning groups predicts their investment of study time. We followed 323 college students across three problem-based courses, assessing their interest in problems both prospectively (before solving) and retrospectively (after solving). Students also reported their independent study time per problem. Results showed that prospective and retrospective interest ratings were weakly correlated. Only retrospective interest predicted study time. Proximity to exams increased study time, but this effect did not interact with interest. These findings suggest that initial situational interest does not sustain effort. Instead, retrospective interest—shaped by students’ experiences—better explains study time investment, highlighting the importance of maintaining interest over time rather than relying on initial curiosity.

Purpose The primary purpose of this study is to understand how social media affects the stock market through the Market Uncertainty Unit on X (formerly known as Twitter) in both the short and long run. Design/methodology/approach We use an autoregressive distribution lag (ARDL) model. This method is common in financial research and is particularly useful for analyzing how quickly the market reacts to changes in the economy or investor sentiment. By analyzing monthly dataset since 2011, we study the impact of social media sentiment on five major US stock indices, such as the S&P 500, NASDAQ, USA, NYSE and Dow Jones Industrial Average (DJI). The explanatory variables include the Social Media Uncertainty Index (SMX), real effective exchange rate (REX), consumer price index (CPI), interest rate (IR), industrial production index (INPT) and a linear deterministic TREND variable. Findings We find that whenever SMX rises, stock market volatility is also amplified, especially in the short run. Fluctuations in social media sentiment are often a strong signal of short-term stock price changes, especially when discussing economic policy or corporate earnings. Originality/value The fact that a few emotional or controversial tweets from executives can directly pull stock prices up and down further illustrates the importance of digital communication in investment decisions. Investors and financial analysts can use social media sentiment as an aid tool to help them more accurately predict market movements and reduce investment risk.

This study aims to: (1) identify and analyze the development of Third Party Funds (DPK), inflation, savings interest rates, Gross Regional Domestic Product (GRDP) at constant prices, and regional expenditure across Indonesian provinces during 2019–2023; and (2) examine the influence of inflation, savings interest rates, GRDP at constant prices, and regional expenditure on Third Party Funds in the same period. The research employs panel data regression analysis using EViews 12 for data processin.The results show that (1) the highest average growth of Third Party Funds (DPK) was recorded in South Kalimantan (11.89%), while the lowest was in Banten (-10.87%). The highest average inflation occurred in East Java (3.7%) and the lowest in Papua (2.1%). The savings interest rate peaked in 2019 at 1.17% and declined to its lowest level in 2022 at 0.37%. The highest GRDP growth was found in North Maluku (16.41%) and the lowest in West Papua (1.16%). Similarly, North Maluku also recorded the highest regional expenditure growth (14.08%), while West Papua experienced the lowest (-17.24%), reflecting economic disparities across regions in Indonesia. (2) The regression analysis reveals that GRDP at constant prices and regional expenditure have a significant and positive effect on Third Party Funds, while the savings interest rate has a significant and negative effect. In contrast, inflation shows no significant effect on Third Party Funds.

The housing market in Malaysia has experienced significant upheaval over the past twenty years, driven by consistent inflows of foreign direct investment (FDI) into the building sector. Although these investments have catalyzed urban modernization and economic expansion, they have also been linked to escalating housing prices and diminishing affordability, especially in metropolitan areas. This study examines the association between foreign direct investment in construction and housing prices in Malaysia, determining whether foreign investment serves as a catalyst for housing price inflation or promotes sustainable urban growth. The study utilizes quarterly data from the first quarter of 2009 to the fourth quarter of 2023, employing a Vector Error Correction Model (VECM) to analyze both short-term and long-term dynamics among the housing Price, Foreign Direct Investment in construction sector, real interest rate, and income. Unit root tests indicate that all variables are integrated of order one, I(1), whereas Johansen cointegration results demonstrate a stable long-run equilibrium relationship among them. The results indicate that foreign direct investment in construction has a positive and considerable impact on home prices, whereas real interest rate indicates a negative effect on price fluctuations. Income growth demonstrates a beneficial although insignificant impact. Granger causality studies demonstrate a unidirectional causal relationship from foreign direct investment (FDI) to housing prices, confirming that property market of Malaysia is primarily driven by investment rather than income. The study suggests that whereas foreign direct investment (FDI) fosters construction expansion, it simultaneously impairs affordability constraints. Policymakers ought to implement focused FDI screening, bolster macroprudential instruments, and improve domestic construction efficiency to guarantee equitable and sustainable housing development.

Abstract: Tier III banks in Kenya have not been stable in their performance because they are exposed to system risks like the volatility of interests. These are banks that mainly reach small businesses and low-income earners, and they cannot take a lot of shocks in changes in credit expenses. This paper has investigated how interest rate volatility impacted the performance of Tier III banks in Kenya in the years 2004-2024. The key performance indicator used was Return on Assets (ROA). The sources of secondary data included Central Bank of Kenya (CBK), Kenya National Bureau of Statistics (KNBS) and the published financial statements of the 22 Tier III banks. Descriptive statistics revealed that the interest rates were between 6 and 18 with the mean of 9.46 and a standard deviation of 2.54, which revealed great volatility. During the same time, ROA was 1.1 on average, ranging between -0.41% and 2.37 with not all years showing positive returns. Correlation analysis showed that there was a weak positive relationship between interest rates and ROA (r = 0.191), which indicated that an increase in interest rates increased net interest margins temporarily. Regression analysis, however, revealed that ROA had a negative and slightly significant correlation with interest rates (= -0.003111, = 0.056), which meant that increased rates eventually caused the bank to become less profitable. The explanatory power of the model was R2 = 0.117 with a total significance of F = 4.12 (p = 0.056). The results showed that there could be short-term positive outcomes on lending rates as it could increase interest income, but the long-term impact of interest rate volatility was a negative outcome on the financial performance of Tier III banks in the form of higher loan defaults and decreased credit uptake. The research concluded that interest rate volatility has been a major risk issue that was weakening the stability of small banks in Kenya. It suggested that the CBK should take up the stable interest rate policies and Tier III banks must enhance credit risk management, diversify their income sources as well as the capital buffers to survive the volatility.

ABSTRACT Interest rates are fundamental in macroeconomic modeling. Recent studies integrate the effective lower bound (ELB) into vector autoregressions (VARs). This paper studies shadow‐rate VARs by using interest rates as a latent variable near the ELB to estimate their shadow‐rate values. The study explores machine learning models, such as the Bayesian LASSO, and extends the analysis to include homoscedastic and stochastic volatility shadow‐rate VARs. It also examines the integration of shadow rate with vintage‐specific long‐run assumptions derived from the Survey of Professional Forecasters (SPF). The paper analyzes 16 shadow‐rate VARs with 20 US variables, using real‐time data from 2005 to 2019 and assesses their predictive accuracy for both point and density forecasts. The findings indicate that shadow‐rate models can enhance predictive accuracy for both short‐term and longer term horizons across macroeconomic and financial variables. These models could be of use for central banks and policymakers.