Muslum Mursalov

Type of article: Research Article

Abstract
This study investigates the causal relationship between research and development (R&D) financing and economic growth in Hong Kong over the period 1998–2022. It examines both public and private R&D expenditures, along with the number of researchers involved in R&D, to evaluate their influence on GDP per capita. Utilizing advanced time series econometric techniques, including the Toda-Yamamoto causality approach and cointegration analysis, the results reveal a statistically significant unidirectional causality from R&D expenditure to GDP per capita (χ² = 26.443, p < 0.01) and from researchers in R&D to GDP per capita (χ² = 38.164, p < 0.01). Additionally, feedback effects were observed, with GDP per capita also causing R&D expenditure (χ² = 17.471, p < 0.01), and R&D expenditure influencing the number of researchers (χ² = 6.718, p < 0.01). These findings highlight the dynamic interplay between financial inputs and human capital in R&D and underscore the importance of sustained investment and a skilled research workforce in fostering long-term economic growth. The evidence supports the strategic role of R&D policy in enhancing productivity and promoting economic sustainability in knowledge-based economies.

Type of the article: Research Article

Abstract
Renewable energy expansion is a cornerstone of environmental policy, yet empirical evidence on whether restricting international public finance for fossil fuels accelerates this transition remains scarce. This study assesses whether international public finance restrictions on fossil fuels promote renewable energy development across a panel of 128 countries, and how banking system depth moderates this policy effect. The analysis employs fixed-effects models with country-specific linear trends, validated through event-study, placebo, and first-difference checks, drawing on World Bank and Clean Energy Transition Partnership data. The results indicate that fossil fuel finance restrictions increase the share of renewable energy in total final energy consumption by 11.5-15.3 percentage points (p < 0.05), representing a relative increase of 40–53% compared with the sample mean of 28.9%. The first-difference estimator confirms that restrictions add nearly 1 percentage point to annual growth in the renewable energy share (β = 0.908, p = 0.013). The effect concentrates on non-hydro technologies: excluding hydropower, the estimated increase reaches 15.1 percentage points (p = 0.013), indicating that the policy primarily stimulates solar and wind deployment. Banking system depth significantly moderates these effects (p < 0.05): the policy impact is virtually zero where domestic credit is below 25% of GDP, but reaches 12.9 percentage points where credit exceeds 100% of GDP. This conditional pattern shows that fossil fuel finance restrictions deliver meaningful environmental gains only where the financial system can redirect capital toward renewable energy investment.

Type of the article: Research Article

Abstract
With five years remaining to the 2030 deadline of the United Nations Sustainable Development Goals, the relationship between monetary policy and SDG progress remains largely unexplored. This paper aims to quantify the association between short-term policy rates and SDG 1, SDG 8, and SDG 10 achievement across high-income, upper-middle-income, and low- and lower-middle-income economies. The analysis draws on a panel of 129 economies over 2000–2023, combining SDSN SDR2025 goal scores, IMF interest-rate series, World Bank WDI controls, and WGI 2.0 indicators (2,563 country-year observations), estimated using two-way fixed-effects regressions with country-clustered standard errors and eight robustness blocks. First, higher policy rates show a modest and consistent positive association with SDG 8 across income groups (β ≈ +0.045, all p < 0.10), robust to two-period lags and a dynamic LSDV re-specification. Second, the pooled association with SDG 1 is null, but interaction estimates reveal significant income-group heterogeneity: within-HIC β = +0.412 (p = 0.006) and a significantly weaker UMC association (interaction β = −0.590, p = 0.002), with a negative but insignificant net UMC estimate (−0.178, p = 0.20). Third, the aggregate SDG Index is negatively associated with the policy rate only in the UMC sub-sample (β = −0.048, p = 0.027), and the SDG 8 association disappears when real or lending rates replace the policy rate – consistent with a signaling interpretation rather than an identified mechanism. Assessments of monetary policy in the SDG context should distinguish between goals with consistent associations and goals whose association varies significantly with income group.