Microfinance loans have long been associated with relatively high interest rates. There is a wide variation of interest rates charged by microfinance institutions (MFIs) across countries, as well as some dispersion of interest rates across MFIs within the same country. The source of interest rate variation can result from institution specific characteristics such as, average loan size and the composition of female borrowers. The dispersion in prevailing interest rates in the formal financial sector across countries may partially contribute to the variation of microfinance interest rates across countries. I use yield on gross loan portfolio as a proxy for the average interest rate on loans, the average loan balance as a measure of average loan size, and lending rate for commercial loans to represent the interest rate in the formal financial sector. This study attempts to analyze the dispersion of interest rates on microfinance loans by showing its association with loan size, female composition of borrowers, and the prevailing lending rates. Using a large panel of 1,531 MFIs, I show that microfinance interest rates have a statistically significant negative relationship with loan size, and a positive association with commercial lending rate and the female composition of borrowers.

This study examines the impact of the Russia-Ukraine conflict, which began on February 24, 2022, on natural gas prices and supply security in major global markets. Six months after the conflict's onset, natural gas prices surged by an average of 78.65% across international markets. Notably, prices in the European Union, Russia, the United Kingdom, Japan, and South Korea saw substantial increases, while price hikes in China, the United States, and Australia were comparatively smaller. Despite these price fluctuations, the security of natural gas supply in key international markets remained largely unaffected. Using the Differences-in-Differences (DID) method, the study analyzed the conflict's impact on supply security, employing a mediation effects model to examine the roles of supply, demand, and price. The findings reveal that the conflict significantly reduced natural gas supply security, with negative effects on both supply and demand, although price changes did not mediate this reduction in supply security. Furthermore, the regional impact on supply security was minimal, likely due to the high integration of the global natural gas market. Overall, the Russia-Ukraine conflict notably influenced natural gas supply security by affecting supply and demand factors.

Forty-five UK universities were approached, drawn from 21 universities whose client technology/knowledge-transfer firms perform consistently well (category 1 universities), and 24 universities whose client technology/knowledge-transfer firms perform consistently poorly (category 2). Contact was established with staff in the Technology Transfer Office (TTO) or similar department, resulting in 72 persons identified as either “leading” TTO staff or “operational” TTO staff. These individuals were subject to semi-structured interviews around a 10-point questionnaire to arrive at consensus opinions. Results indicate that independently of whether the university is regarded as “entrepreneurial” or not, the TTOs of category 1 universities are more ambidextrous than those of category 2 universities.

Using data from the Japanese government bonds and stock markets, this study examines the predictability of Japanese recessions based on a probit model with instrument variables. By decomposing the term spread into the expected short-term interest rate and the term premium, this study analyzes the relationship between the components of the term spread and recessions. The results show that the predictive power of the term spread for recessions has declined since 1999—when Japan began employing an unconventional monetary policy. Additionally, stock market capitalization relative to nominal GDP is a useful predictor of recessions.

The use of digital technologies like artificial intelligence, robotics, or smart devices can be expected to go hand in hand with higher productivity and lower trade costs, and, therefore, to be positively related to export activities. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union to shed further light on this issue by investigating the link between the digitalization intensity of a firm and extensive margins of exports. We use a new machine-learning based regression method, Kernel-Regularized Least Squares (KRLS), which effectively handles non-linear relationships in models and does not impose any restrictive assumptions for the functional form of the relation between margins of exports, digitalization intensity, and any control variables. We find that firms which use more digital technologies do more often export, do more often export to various destinations all over the world, and do export to more different destinations.

We propose an open-access innovation index for the U.S. states. This index was built by classifying into four core areas the twelve more important indicators, inputs, and outputs, that are widely accepted in the literature as the most relevant for measuring innovation. We consider the indicators aggregated in the areas of human capital and business environment as the inputs that create knowledge and influence the promotion of innovation, while those in areas of engagement and efficiency as the outputs that are all those outcomes and improvements related to the innovation process. As an example of potential uses of our index, we ran a basic econometric experiment using the economic growth rate as the dependent variable. Despite the results being qualitatively consistent with the literature, we suggest further research using our index and other methodologies. We included in the appendix the overall index score and ranking from 2000 to 2015.

This study documents the relationship between economic freedom and unauthorized immigration to the U.S.A. and tries to answer a still-in-debate question, what motivates people to unauthorizedly migrate? Using the generated instrument variables methodology, and a data panel of 15 countries and 16 years, the endogenous variable is the gap in economic freedom between the country of origin and the U.S., and the dependent variable is the unauthorized immigrant’s growth rate. The results show that for each 10% improvement in economic freedom in the country-of-origin unauthorized immigration decreases around 7%. Estimations are robust even after using other covariates and external instruments. The main conclusion is that economic and social factors play a significant role in shaping migration patterns and that the difference in economic freedom between the country of origin and the U.S. plays a fundamental role in deciding to unauthorizedly migrate

Green finance is an important driving force to promote green innovation and achieve green development. In order to deeply explore the internal relationship between green finance and green innovation efficiency, this paper selects China's provincial panel data from 2012 to 2023, uses the entropy method and super efficiency SBM model to measure the green finance development index and green innovation efficiency of each province, and on this basis, chooses to construct the spatial Durbin model with fixed effects for empirical analysis and effect decomposition. The results show that: (1) From 2012 to 2023, the development level of green finance and green innovation efficiency of China's provinces will increase year by year with the development of economic base; (2) The green innovation efficiency of provinces with better economic foundation and perfect infrastructure is also at a high level; (3) The level of green finance development, productivity, fiscal revenue and expenditure and urbanization not only have a direct effect on the green innovation efficiency of the region, but also have a spatial spillover effect on the neighboring regions.

This paper employs a two-way fixed effects model and uses panel data from 31 provinces of China between 2012 and 2022 to empirically analyze the impact of digital inclusive finance on China's Outward Foreign Direct Investment (OFDI). The study finds that, overall, the development of digital inclusive finance in China significantly promotes OFDI. Its sub-dimensions, including coverage breadth and usage depth, have a significant positive impact on OFDI across Chinese provinces. Further analysis reveals that the sub-dimensions of usage depth, such as credit and payment, also have a significant effect on OFDI in various provinces. In addition, the control variable of economic development level significantly positively influences OFDI in China. Regional regression results indicate that the development of digital inclusive finance in central and western China significantly promotes OFDI in these regions, while the effect is not significant in the eastern region. Policy Recommendations: China should accelerate the development of a digital inclusive finance system and promote financial innovation. It is crucial to focus on the coordinated development of various digital inclusive finance indicators, narrow the financial service gap between regions, and thus foster the long-term development of China's outward foreign direct investment.

Recently, some authors have found derivations and applications of the golden ratio in economics science. Based on previous models of Financial Gravity (FG) and generalizing them, this paper proposes the maximization of pure flows after charges as a way for applying the golden ratio in the sales-costs of production ratio in competitive equilibrium, leading to an optimal unitary charge of 0.2361… with many economic applications in monetary economics as well as in finance, public economics and taxation, migration flows, VAT on goods and services and commercial trading. Other applications are also suggested for further research. This paper can be useful for mathematical and applied economists, public financiers, bankers and policy and lawmakers.