While climate change affects agricultural production globally, scarce literature has quantified the impacts of climatic factors on paddy yields with attention to specific water regimes, climatic zones, growth periods, and crop seasons. This study aimed to identify the effects of various climatic variables at different plant growth phases (growing and harvesting), crop seasons (Maha and Yala) [In Sri Lanka, there are two main crop seasons. Maha is the major cultivation season covering the months of October to March, and Yala is the minor cultivation season covering the months of April to September], and water regimes (major irrigation, minor irrigation, and rainfed) in three climatic zones (dry zone, intermediate zone, and wet zone) of Sri Lanka. A district-wise annual panel dataset was constructed for a 39-year period (1981 to 2019) covering 18 districts and analyzed by panel regression methods. The results showed that temperature had significant non-linear effects on yields in the dry and intermediate zones. Variation in temperature decreased yields more in the dry zone than in other zones. Rainfall significantly reduced yields in the dry and wet zones, whereas it increased yields in the intermediate zone. Rainfall fluctuations decreased yields in the wet zone more than in other zones. These findings suggest a need for dissemination of climate-smart agriculture practices by considering the characteristics of each water regime, particularly in the dry zone. For rainfed paddies, a crop insurance scheme should be introduced to reduce crop losses due to harsh climatic events. Complementary policies, such as improvement of irrigation systems and provision of timely weather forecasts, can support smallholder paddy farming.
This study analyzed the efficiency of residential electricity demands from 1990 to 2015 across the electrical supply regions of Japan. Specifically, I utilized a stochastic frontier analysis to statistically identify the determinants of the efficiency of residential electricity demands. The analysis revealed that a decline in average household size improves the efficiency of electricity demands, whereas a rise in the aging of household members worsens it. Furthermore, this study showed that the efficiency of electricity demands improves in warmer regions because of increased cost consciousness in cooling demands, whereas it deteriorates in colder regions because of the complementary use of various heating devices. A shift in Japan’s energy policy following the 2011 Great East Japan Earthquake has not significantly affected the efficiency of residential electricity demands. In other words, no structural changes have occurred in the efficiency of electricity demands during the observation period. As such, long-term trends within this sector in Japan include a decline in the average household size and a rise in population aging. Therefore, these findings provide important insights into Japan’s future trends in terms of energy demands.
Borrowing constitutes the capital structure of a firm. Also, impacts of borrowing on corporate performance differ from one nation to another. This study used data and multiple regression analysis to determine the impacts and sensitivity of borrowing on related risks in corporate performance. Data included a sample of manufacturing companies from the Tokyo Stock Exchange (TSE) and manufacturing companies from some top stock exchanges in Sub-Saharan Africa (SSA) from 2016 to 2019. The results showed that borrowing affects corporate performance. Due to differences in interest rate, inflation rate, governance and fluctuating economic conditions, impacts and risks of borrowing in SSA are higher than in Japan. The results also indicated that financial performance can be optimized by mitigating interest rate risk, exchange rate risk, market risk and fluctuations in economic conditions. In conclusion, the negative impacts of borrowing on corporate performance are more substantial in SSA than in Japan.
This Special Feature investigates the social, economic, and spatial impacts of the COVID-19 pandemic in Turkey and highlights the factors differentiating Turkey from the other countries. The articles contributing to this Special Feature are classified into three main parts. The first group of articles addresses spatial implications of the COVID-19 pandemic in Turkey with a specific focus on the place-based factors affecting the spread of the pandemic, the determinants of pandemic-induced changes in intracity mobility, and the use of social media to forecast commercial real estate figures during COVID-19. The second group of articles investigates the social and economic implications of the COVID-19 pandemic and diversely affected economic sectors in Turkey. These articles analyze the vulnerability and resilience of regions and diversely affected economic sectors with a specific focus on the housing market that displays an opposite trend to international tendencies regarding transaction volumes and private rental housing prices. The third group of articles considers the economic impact of the COVID-19 pandemic from an international perspective. These articles analyze the impact of the COVID-19 pandemic on international trade with a specific focus on exports and the fragility of the global trade structure and network in the framework of global value chains. Analyzing the impacts of COVID-19 from different perspectives, the articles in this Special Feature reveal the factors differentiating Turkey from the other countries and highlight the challenges.
This study examined how Sri Lankan cooperative banks performed in changing markets and environmental conditions, including the COVID-19 pandemic. We analyzed quarterly financial data for 103 cooperative rural banks (CRBs) between 2016 and 2020 to estimate technical efficiency and total factor productivity (TFP) using the input distance function with multiple outputs. The technical efficiency (TE) of CRBs declined from 99 to 85% over the period and differences in TE between banks increased substantially. TFP decreased substantially, by 38%, so for further analysis, TFP change was separated into a three component-scale change, technical change, and technical efficiency change. According to TFP decomposition, the dominant factor contributing to this decline was the scale change. The loan relief program enacted during the COVID-19 crisis, as well as increased competition in the market, may have reduced the size of operations, thus possibly contributing to this decline. The second component, technical change was overall positive, but minute likely due to the reluctance of cooperative banks’ to adopt new technologies. The third component technical efficiency change was negative throughout the period, likely due to increased operating expenses and non-performing loans. These findings suggest the need for a more market-sensitive government intervention, adaptation of modern technology, and comprehensive human resource development to enhance the performance of CRB operations.
Rent prices have a strong relationship with economic factors in addition to the structural and environmental characteristics of housing stocks. Previous research demonstrated that impacts of unexpected and sudden circumstances such as war and epidemics on urban housing markets relate to their effects on the economy. Following the first COVID-19 case in Turkey, which was officially announced on 11 March 2020, changes in both housing preferences and economic structure have significantly affected the rental housing market due to the pandemic conditions. To highlight challenges in the rental housing market, this study addressed how the COVID-19 pandemic has influenced rental housing prices in 81 provinces of Turkey using the big data set of Endeksa, a private real-estate platform in Turkey. The data set was descriptively analyzed through four main periods identified on the basis of changing COVID-19 pandemic regulations and implementations in Turkey. Average rent prices of Turkish provinces during the identified periods were compared using ArcGIS 10.6. to show how private rent prices changed during the pandemic. The findings demonstrated that the unit rent prices generally increased from March 2020 to December 2021 throughout the whole country. Furthermore, the findings highlighted that while metropolitan cities have the highest unit rent price, the highest rent price rise occurred in provinces located in Central and Eastern Anatolia. This study contributes to the literature on how sudden shocks such as pandemics affect rent prices in free rental markets. In addition, it shows how the impacts of the COVID-19 pandemic on the rental housing market differ from country to country by revealing the increasing trends in Turkey.
This study investigated pollution haven hypothesis (PHH) validation and existence of the environmental Kuznets curve (EKC) hypothesis in Bangladesh. The study used CO2 emissions as the key indicator of environmental pollution. Moreover, we considered relevant explanatory variables such as foreign direct investments, trade openness, financial development, gross fixed capital formation, energy consumption and urbanization to achieve our goals. Covering the time series data from 1986 to 2018, the autoregressive distributed lag (ARDL) approach was applied. The findings revealed a long-run cointegration between the considered variables, and the ARDL results cannot validate the PHH in Bangladesh. These results contribute to the existing literature by concentrating on the EKC hypothesis for financial development purposes. Furthermore, we found that urbanization, gross fixed capital formation and trade openness positively influence CO2 emissions, while energy use reduces CO2 emissions. These findings suggest that Bangladesh should take advantage of the invalidity of the PHH and introduce eco-friendly urbanization planning to mitigate detrimental effects of environmental pollution.
In December 2019, COVID-19 infections first occurred in Wuhan City, China, after which it rapidly spread throughout the world. Today, COVID-19 has become a major disaster affecting countries physically, socially, and especially economically. However, reasons behind the spread of COVID-19 are still unclear. Therefore, many scholars from different disciplines try to understand the various leading indicators. Our study aimed to reveal place-based factors affecting COVID-19 incidences in Turkey while addressing and analyzing a set of indicators (physical, natural, economic, demographic, and mobility based) within the scope of the recent research findings in the literature on the COVID-19 Pandemic. Following this purpose, we addressed 81 provinces of Turkey using city-level data obtained from the Ministry of Health, and employed global and local regression methods through ArcGIS and GeoDa: Ordinary Least Square, Spatial Lag Model, Spatial Error Model, and Geographically Affected Weighted Regression to highlight place-based factors affecting the spread of the Pandemic. The results of our analyses demonstrated that three factors: (1) population density, (2) annual temperature, and (3) health capacity; are related to the COVID-19 incidences in Turkey. Our results also demonstrated that the impact of these factors causes varying spatial effects within the country, especially in the West–East direction. Although these results provide a base for future studies, COVID-19 is still spreading with several mutations. Therefore, the reliability of produced models and the effectiveness of factors should be retested using new and updated data for cities and at other geographical scales.