The expansion of financial technology promises greater financial inclusion, yet for many female street vendors (pedagang kaki lima/PKL) in Indonesia, it has instead created a form of digital entrapment. This study employed a qualitative, retrospective case study methodology to investigate the lived experiences of 10 purposively selected women who had engaged with online lending services (pinjol). Drawing on Jan van Dijk’s four-level digital divide framework, we conducted a thematic analysis of in-depth interview data to assess their levels of vulnerability. Findings indicate that the decision to use online loans was not driven by well-developed business strategies but rather by persuasive advertising and immediate personal needs. Participants frequently misinterpreted the presence of OJK (Financial Services Authority) logo as a universal guarantee of safety, while lacking the skills to critically evaluate interest rates, loan conditions, and data-privacy risks. The perceived affordability and accessibility of these platforms came at a significant cost, particularly in terms of personal data exposure, which further exacerbated participants’ financial and emotional vulnerabilities. Rather than fostering financial independence, online lending entrenched a “gali lubang tutup lubang” (robbing Peter to pay Paul) cycle of indebtedness that undermined their livelihoods, mental well-being, and social environments. This study shows that for women working in the informal sector, fintech’s promise of inclusion often masks structural dynamics that reproduce exploitation and deepen precarity in developing-country contexts.

This study aims to analyze the effect of economic growth, interest rates, and inflation on the stock prices of manufacturing companies in Indonesia from 2021 to 2023. The methodology used in this study is a quantitative approach utilizing secondary data in the form of annual financial reports of companies obtained from the official website of the Indonesia Stock Exchange (IDX) as well as other supporting sources. The sample selection in this study was carried out using a random sampling method, and the analysis was conducted using SPSS software. The results of the study indicate that economic growth and interest rates have a significant effect on stock prices, thus H1 and H2 are accepted; conversely, inflation does not have a significant effect on stock prices,so H3 is rejected

Interest rate risk supervision and bank capital management: What can the new prudential standards tell us?

Do zombies rise when interest rates fall: A relationship banking model

Consumer loans are financial instruments that enable individuals to finance needs such as housing, automobiles, education, healthcare, holidays, and daily expenses. These instruments both influence and are influenced by the macroeconomy. This study explores the relationship between consumer loans and macroeconomic factors. Specifically, it examines the connection between consumer loans, economic growth, and credit risk using sector and bank group data on consumer loans, non-performing loan ratios, GDP, interest rates on consumer loans, CPI, real exchange rate, and money supply from 2007 to 2023, employing ARDL (Autoregressive Distributed Lag) and Granger causality analyses. The findings indicate that while consumer loans support short-term growth, they do not promote long-term growth, except for consumer loans from foreign bank groups. Nevertheless, the role of consumer loans in reducing credit risk through distribution remains significant.

In the branch banking system, branches with surplus funds cannot be profitable without an internal fund transfer pricing (FTP) system. Therefore, a dynamic FTP model is critical to enhance a bank’s sustainability. This article has designed a market-oriented multiple FTP model by factoring in liquidity risk, market interest rate, credit demand, and portfolio diversification. The FTP rates are estimated using the 151 branch-level daily data of a bank in India. We reduced the endogeneity issue related to variable selection with the 2SLS system equation. The findings suggest that dual-functioning branches are profitable if they reduce their fund borrowings from the corporate head office (HO). Corporate treasury provides liquidity support to banks, but their profit gets impacted by the increase in the policy and HO-transfer rate. The study showed that corporate spread is significantly affected by increased liquidity cost and market borrowing rate. It is also empirically established that internal FTP pricing may hamper branches’ earnings when branch managers mobilize funds beyond the cost of lending as per FTP rates. The dynamic FTP model is linked to the yield curve, making it market oriented and enabling managers to price products effectively. JEL Codes: G21, D02

Exports play a pivotal role in Indonesia’s economic growth, with crude palm oil (CPO) being a key contributor to international trade. A decline in CPO export value could potentially weaken economic performance. This study investigates the influence of production, global prices, exchange rates, and interest rates on Indonesia’s CPO export value using the Error Correction Model (ECM) for the 1995–2024 period. The findings indicate that production has a significant positive impact on export value in both the short run and the long run. Global prices and exchange rates also exert significant effects across both horizons, while domestic interest rates show an indirect influence. Overall, the study confirms that Indonesia’s CPO export dynamics are shaped by a combination of production factors and macroeconomic variables, with distinct patterns of relationship between short-run and long-run contexts.

Empirical studies from emerging markets such as Nepal and other South Asian countries report inconsistent and often contradictory findings regarding firm-specific determinants of share prices. To address these issues, the researchers adopted a correlational and explanatory research design so as to examine the relationship and explanatory power of firm-specific determinants over market price per share (MPS) of Nepalese commercial banks. Sixteen commercial banks were selected using judgmental sampling, and balanced panel data covering 2019/20–2023/24 were collected from their annual reports. Ordinary least squares (OLS) regression revealed significant positive effects of cash reserve ratio (CRR), capital adequacy ratio (CAR), and total assets (TA) on MPS, while return on assets (ROA) showed a positive but non-significant effect. Conversely, weighted average interest rate spread (WAIRS), credit-to-deposit ratio (CDR), and non-performing loan ratio (NPLR) showed significant negative effects on MPS. These findings provide valuable insights for investors, helping them make more informed decisions.

This study examines Romania’s real estate market (2003–2023), analyzing economic variables’ impact on housing demand and investment trends through PLS-SEM and regression analysis. It addresses housing affordability challenges, particularly for younger generations, highlighting rising prices, increasing costs, and limited mortgage access as key barriers to homeownership. Furthermore, it explores the socio-economic implications of affordability issues, emphasizing their links to inequality and financial vulnerability. This study examines the shift from consumption to investment in the market, emphasizing the rising demand for real estate. It explores the impact of the sharing economy, particularly short-term rental platforms like Airbnb, on housing prices and affordability. Analyzing economic variables within a supply-demand framework, it distinguishes between new and existing housing stock while incorporating a LCC perspective. The research identifies high-growth market segments, providing insights for policy formulation and investment optimization. It contributes to the debate on government interventions in housing, evaluating whether support should target supply or demand for affordability. Using an ECM, the study examines investment impacts, particularly capital gain speculations, on housing demand, assessing interest rate fluctuations and mortgage dynamics. By integrating historical and current housing prices, it improves market analysis and forecasting, clarifying economic variables’ influence on investment behaviour and stability. First published online 28 January 2026

ABSTRACT In recent years, Non-Banking Financial Companies (NBFCs) have emerged as strong competitors to traditional banks in the Indian lending market. Customers increasingly prefer NBFC loans due to faster processing, minimal documentation, flexible eligibility criteria, and personalized services. While banks continue to offer lower interest rates and greater institutional trust, NBFCs have successfully attracted borrowers by focusing on convenience, accessibility, and quick disbursal. The present study aims to analyze the key factors influencing customer choice of NBFC loans over bank loans. The study examines demographic, behavioral, and service-related factors such as loan processing time, documentation requirements, interest rates, customer service quality, and digital accessibility. A descriptive research design is adopted using both primary and secondary data. Primary data is collected through a structured questionnaire, while secondary data is sourced from research journals, RBI reports, and financial publications. The findings of the study provide valuable insights for NBFCs, banks, and policymakers to understand borrower preferences and improve loan products and services in a competitive financial environment. Keywords: NBFCs, Banks, Customer Preference, Loan Services, Financial Institutions, India

This study examines how economic policies influence the purchasing decisions of Sri Lankan consumers in the motor vehicle market. Monthly new vehicle registrations are used as a proxy for overall consumer demand. Data on vehicle registrations, along with monetary, fiscal, and socio-economic indicators from 2017 to 2023, were collected from multiple sources, including the Central Bank of Sri Lanka, Sri Lanka Customs, the Department of Motor Traffic, and the Sri Lanka Tourism Development Authority. The analysis employs several econometric techniques, including the Johansen cointegration approach, the Vector Error Correction Model (VECM), and Wald causality tests, to examine relationships among the variables. The findings indicate that consumer demand for motor vehicles is closely associated with key monetary policy variables, selected fiscal indicators, and socio-economic stability, particularly in the long run. Real interest rates, motor vehicle tax revenue, and the government wage index exert significant negative effects on vehicle demand in the long term. The VECM results show that deviations from long-run equilibrium adjust at a rate of 46.8 per cent per month, implying stabilisation within approximately 1.1 months. Overall, monetary factors exert a stronger influence on vehicle purchasing behaviour than fiscal policies, highlighting the importance of monetary stability and socio-economic improvements in policy formulation.

This research examines the impact of positive crude oil revenue shocks on Russia’s macroeconomic policy and economic development, analyzes the effects of macroeconomic policy on the economy, and compares these effects across two subsamples (2005–2013 and 2015–2019). The study proves that the full 2005–2019 model fails to capture the transmission responses of policy and macroeconomic variables after the significant structural shift in the post-2014 period, while subsample models each provide a better fit and more accurate results. Our empirical research provides the following insights: First, after 2014, fiscal expansion shifted from an anti-inflationary tool to an inflationary driver as well as a depreciating force on the national currency. Second, after 2014 the monetary policy’s tight stance became explicitly anti-inflationary compared with its direct opposite effects before 2014. Third, after 2014, the central bank’s more dominant inflation-targeting regime tightened the constraints on fiscal policy. Fourth, the Russian Federation’s economic dependence on oil diminished after 2014. Finally, macroeconomic policy (government expenditure and key interest rate) shifted from procyclical to countercyclical in response to oil revenue shocks after 2014.

ABSTRACT Conventional wisdom holds that lowering a home country's interest rate relative to another's will depreciate the domestic currency. We document that, at business‐cycle frequencies, U.S. forward guidance monetary policy easings had the opposite effect during the Great Recession. We attribute this effect to calendar‐based forward guidance that signaled economic weakness, resulting in a “flight‐to‐safety” effect and lower expected U.S. inflation. We also document cross‐currency heterogeneity: a surprise U.S. rate cut induced a larger appreciation of the dollar against currencies that typically depreciate more when the world economy is contracting. We build a model that can reconcile these findings.

This study aims to analyze the influence of inflation and interest rates (BI Rate) on consumption credit in Indonesia, with global economic policy uncertainty as a moderating variable. This study uses secondary data in the form of monthly time series data from June 2015 to March 2025 published by the Financial Services Authority (OJK), Bank Indonesia, and the Economic Policy Uncertainty Index. Multiple regression analysis was applied to estimate the relationship of each variable, accompanied by normality, multicollinearity, and heteroscedasticity tests, so that it met the requirements for a valid and robust regression. The results of the study show that inflation has a negative and significant influence on consumption credit, while interest rates also have a negative but insignificant influence. Global economic policy uncertainty has proven to be able to moderate the negative influence of inflation on consumer credit, so that the negative impact is weaker when uncertainty is greater. Meanwhile, the role of the moderation of global economic policy uncertainty on the relationship between interest rates and consumption credit does not appear significant. Regression analysis also showed that models that included moderation variables were better able to explain the variation in consumption credit distribution, which reached 51.3%.

The main objective of this study is to examine the effect of interest rates and inflation on stock returns of different industries in the Tehran Stock Exchange. In recent years, economic fluctuations caused by increasing inflation rates and changes in bank interest rates have caused widespread concerns among investors, financial managers, and economic policymakers. This study employs multiple regression models and vector error correction models (VECM) to examine the short-term and long-term relationships between variables. In addition, GARCH models are used to analyze the stability and volatility of stock returns against inflation and interest rate shocks. The results of the model estimations show that the inflation rate has a significant and mainly negative effect on stock returns in most industries, especially in those with high dependence on imports or foreign raw materials. On the other hand, the interest rate also has a significant negative effect on the returns of capital-intensive and financing-dependent industries. Based on the findings of the VECM model, there is a long-term relationship between inflation and stock returns in some industries, which is consistent with Fisher's theory. This research suggests that economic policymakers should pay special attention to the direct and indirect effects of interest rates and inflation on the capital market. Also, institutional and individual investors should consider the sensitivity of different industries to these variables in their investment strategies.

The volatility of financial markets, the tightening of financing conditions during the global financial crisis, and the rapid growth of fintech technologies have led to the emergence of a new and innovative financial instrument: real estate crowdfunding. The rapid global spread and growing popularity of real estate crowdfunding among investors and project owners have generated interest in research in this area, especially regarding the success factors of such projects. However, to the best of the authors' knowledge, no previous studies have analysed the factors determining the success of real estate crowdfunding projects in Lithuania, thereby emphasising the relevance of this research. The objective of this research endeavour is twofold: firstly, to identify the factors that may influence the success of real estate crowdfunding projects, and secondly, to empirically investigate the effects of these factors in the context of Lithuania's real estate crowdfunding market. To achieve this objective, data from 812 real estate crowdfunding projects on Lithuania's largest real estate crowdfunding platform were utilised. The success of real estate projects was assessed using two variables: the time from project funding in days and the number of investors per project. In addition to these two variables, five project-related factors that may influence the success of such projects were considered. The OLS regression was employed to investigate these effects, and it was revealed that for both indicators of project success, the amount raised, LTV ratio, and project duration had statistically significant effects. It was found that the annual interest rate was a statistically insignificant determinant of real estate project success for both project success indicators. The findings of this research are of paramount importance for project owners seeking to expeditiously and efficaciously raise funding, as well as for crowdfunding platforms in the selection of prospective projects for lucrative financing and the attraction of additional investors.

ABSTRACT This paper tests the effect of financial development (FD) and interest rate liberalisation on macroeconomic volatility (MV) in emerging markets. This study used panel data of 64 countries from 1990 to 2019, and a dynamic panel model (Difference GMM) was applied. Our findings indicate that (i) the impact of FD and interest rate liberalisation on macro fluctuation exhibits a U-shaped bidirectional, (ii) enhancing the financial sector facilitates personal consumption and investment, thereby mitigating MV, (iii) the financial sector serves as both positive and negative effect, and (iv) when FD surpasses a critical threshold, it becomes a catalyst for macroeconomic instability.

On the irrelevance of the concept of a natural rate of interest in a Schumpeter–Keynes perspective

ABSTRACT We investigate the rationale of a rule-based monetary policy in Nepal, applying the modified Taylor (1993, 2001) rule. Our first condition is that uncovered interest parity (UIP) does not hold, and we therefore incorporate the risk premium in the Taylor rule. We also condition that the policy trilemma does not hold by assigning a higher weight to foreign interest rates. We include the simulated risk premium from an earlier publication (Bhatta et al, 2022a). The findings from the generalized method of moments (GMM) model with quarterly data from 2000 to 2020 demonstrate that a modified Taylor rule partially holds for Nepal while the real effective exchange rate (REER) being the dominant factor with negative sign of inflation expectations. These findings indicate that REER characterizes the role of inflation expectations for Nepal, and the monetary policy accommodates remittance income via the REER. The central bank, therefore, should consider foreign factors like REER and foreign inflation targets while setting up the policy rule.

The automotive industry requires fast and accurate sales services, particularly in vehicle credit simulation processes. At Mazda dealerships, credit simulations are still commonly conducted using conventional tools such as printed installment tables or static PDF documents, which often cause delays and calculation errors. This study aims to design and develop a mobile-based vehicle credit simulation application using the Human-Centered Design (HCD) approach and the Flutter framework. The HCD method was implemented through the inspiration, ideation, and implementation stages to ensure that the application meets the real needs of Mazda sales representatives. The application supports flexible credit calculations based on vehicle on-the-road price, down payment, loan tenor, interest rate, and insurance schemes, including All Risk and combination insurance. Usability testing results show that the proposed application significantly improves calculation speed, accuracy, and overall user experience compared to conventional methods. Therefore, the application effectively supports sales performance, minimizes human error, and enhances professionalism in automotive sales services.