Murat Guven

In the pursuit of sustainable development, it is crucial to examine whether technological innovation (TI) creates equitable economic distribution or widens income inequality (II). The study aims to investigate TI’s impact on II in BRICS-T and BRICS PLUS-T countries within the context of the technological Kuznets curve (TKC). Along with TI, financial development is a driving force for economic development, and the research explores FD’s influence on II. To analyze these relationships while accounting for globalization (G), the method of moments quantile regression (MMQR) is used. The study’s findings validate the U-shaped TKC, suggesting that TI, in the initial stage, reduces II. However, beyond a certain threshold, TI² significantly widens II in both country groups. We found that the impact of TI on II was more pronounced in BRICS-T countries than in BRICS-PLUS-T countries, and the inclusion of newly added countries did not significantly affect the U-shaped relationship. Additionally, by enhancing financial inclusion, FD had a substantial and negative effect on II. In contrast, G, which concentrates wealth, was associated with higher II in both groups. This study offers a significant contribution by introducing the TKC in the context of BRICS-T and BRICS PLUS-T countries. Furthermore, the research contributes to the literature by evaluating the influence of FD and G within the context of TKC and applying novel MMQR. The study highlights a pathway to achieving the Sustainable Development Goals (SDGs 1, 7, and 10) and provides a policy framework for strategically allocating funds to technological advancements to reduce II.

The purpose of the study is to compare the effect of country-based and global financial factors on Islamic stock market returns of BRIC (developing) and G7 (developed) country groups covering data from March 26, 2015, to March 31, 2021, for BRIC countries and July 27, 2015, to March 31, 2021, for G7 countries. A newly developed method of moment quantile regression (MMQR) is used to detect the asymmetric effects on Islamic stock market return across bullish, bearish, and normal market conditions, which is essential to better analyzing the stock market return. The outcome demonstrates that exchange rates have a significantly positive effect on stock market returns while CDS has a significant negative impact on the stock market return in G7 countries in both bearish and normal markets. On the contrary, we observe that the link between CDS and Islamic stock returns is negative but statistically insignificant in the case of BRIC. Additionally, we consider the Morgan Stanley Capital International (MSCI) world index and the CBOE Volatility Index (VIX) as the global financial factors. We find that the estimated coefficients of the MSCI world index have significant and positive effects on the stock market return in the case of both BRIC and G7 countries at all quantile levels. VIX has a significant negative impact on the Islamic stock return of the G7 across all quantiles. On the other hand, it has significant negative impacts only in transition (Q6) and a bullish period in the case of BRIC. The outcomes of the research will assist portfolio risk managers, international investors, and policymakers in building diversified portfolios and making investment decisions throughout the market’s busts and booms.

Nations must adapt to the changing and developing world to sustain and develop their competitiveness. Human development and innovation are the two key concepts to increase the competitiveness of a nation. This study aims to examine the relationship between the Human Development Index (HDI), Global Innovation Index (GII), and Global Competitiveness Index (GCI) across different income groups from 2010 to 2019. The main objective is to identify potential variations in these relationships based on the income level of the countries involved. Panel data analyses using Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are conducted to examine the relationships. Additionally, Pairwise Dumitrescu Hurlin Panel Causality Tests are conducted to examine the causal relationships between variables. The results show that HDI has a significant positive effect on GCI in each income group. Improving human development such as raising living standards and providing equal education opportunities for every member of society can contribute to a country’s competitiveness. Moreover, it is found that the effect of GII on GCI varies by income group. Specifically, the results indicate that the effect of GII on GCI is not supported for upper-middle-income countries. Therefore, while developing strategies to increase competitiveness through innovation, it is important to consider the income group of a nation. The findings of this study may assist policymakers, researchers, academics, and politicians to enhance their perspectives and formulate strategic and effective recommendations for action.

In this study, we analyze the effect of selected local and global factors on Azerbaijan's real exchange rate during the period of January 2013 to April 2021, using the quantile regression method that takes asymmetry into account. The results showed that all variables generally influence the real exchange rate at lower quantiles. Specifically, an increase in OILP and CPI leads to a decrease in RER at Q1-Q5 and Q1-Q2, respectively. Furthermore, an increase in RESV and GPR leads to a decrease in RER at Q1-Q2 and Q1, respectively. The effect of the coefficients also decreases as the quantiles increase.

The purpose of this paper is to investigate the effect of gross domestic product per capita, trade openness, renewable energy, energy consumption, foreign direct investment, carbon emission, and oil prices on innovation for selected 11 oil-importing and 11 oil-exporting countries and to compare the results from both country groups to see the differences and similarities. For this purpose, we employ Poisson regression and negative binomial fixed effect techniques from 1990 to 2018. The empirical findings illustrate that all variables are significant except for renewable energy in oil-exporting countries. Trade openness and carbon emission have a significant and negative relationship with innovation, while gross domestic product per capita, energy consumption, foreign direct investment, and oil price have a significant and positive relationship with innovation in oil-exporting countries. Gross domestic product per capita, energy consumption, and carbon emission have a significant and positive relationship with innovation in oil-importing countries, while there is a significant and negative relationship between renewable energy and innovation.

Çalışmanın amacı, Türkiye ve AB ülkelerinin sosyal koruma yardımlarının yoksulluk üzerindeki etkisini panel veri analizi kullanarak incelemektir. Bu bağlamda, 2007 ve 2018 yılları arası 27 AB ülkesi ve Türkiye’ye ait sosyal koruma yardımları olan aile, sağlık, emeklilik ve işsizlik yardımlarının bu ülkelerdeki medyan %50 ve %70 yoksulluk oranlarına göre etkisi Driscoll-Kraay tahmincisi kullanılarak analiz edilmektedir. Analiz sonucunda, sosyal koruma yardımlarından aile ve sağlık yardımlarının yoksulluk oranı medyan %50 ve %70 üzerinde negatif ve istatistiksel olarak anlamlı etkisi bulunmaktadır. Bununla birlikte, emeklilik (yaşlılık, dul/yetim ve engelli) yardımlarının yoksulluk oranı medyan %50 ve %70 üzerinde pozitif ve istatistiksel olarak anlamlı bir etkisinin olduğunu göstermektedir. Son olarak, işsizlik yardımlarının yoksulluk oranı medyan %50 üzerinde istatistiksel olarak anlamlı bir etkisi olmazken, medyan %70 üzerinde yoksulluğu artırıcı etkisi bulunmaktadır.

Weather factors are effective to transmission of various diseases. Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), and kinds of influenza can be given as example these diseases. The novel corona virus which is called COVID-19 is the most dangerous problem all around the world in these days. Early studies have revealed that COVID-19 cases are affected by environmental factors. Therefore, the purpose of this paper is to examine the relationship between the number of novel coronavirus cases and several weather parameters in 81 provinces of Turkey. Mean incubation period of COVID-19 is in question. Thus, this paper also aims to provide better understanding of the exact incubation period in Turkey by employing four different timeframe which are on the day (lag 0), 3 days ago (lag 3), 7 days ago (lag 7) and 14 days ago (lag 14). We have considered population density as a control variable. The dataset cover COVID-19 cases, population density, average temperature, humidity, pressure, dew point, wind speed, and sunshine duration for 81 provinces of Turkey. We find that population density has a positive correlation with COVID-19 cases. We also find that in lag 3, all parameters except for sunshine duration are negatively correlated with COVID-19 cases and significant. However, only 3 parameters, temperature, air pressure and dew point are negatively correlated with COVID-19 cases and significant for lag 0, lag 7 and lag 14. In addition, temperature, air pressure and dew point parameters are negative and significant in all timeframes.