This study investigated the changing land use patterns and their impacts on ecosystem in the Teesta River Basin of northwestern Bangladesh. Although anthropocentric land use patterns, including agricultural land use, settlements, built areas, and waterbody loss, have been increasing in the Nilphamari district, by negatively affecting local ecosystems, they have not been identified by prior research. Limitations of contemporary literature motivated me to work on this crucial ground in the Teesta River Basin in Northwestern Bangladesh. This study applied a mixed research approach to identify the study objectives. Firstly, the land use and land cover (LULC) changes which occurred between 2000 and 2020 were detected using satellite imagery and supervised classification method. In addition to the detection of LULC changes, the study explored the people’s perceptions and experiences about the ecosystem changes resulted from the LULC changes over the last 20 years, conducting stakeholders’ consultations and household surveys utilizing a semi-structured questionnaire. The findings indicated that waterbodies in Nilphamari district have significantly decreased from 378 km2 in 2000 to 181 km2 in 2020. In the same way, the vegetation coverage has reduced 187 km2 between the years 2000 and 2020. On the contrary, agricultural lands (croplands) have increased from 595 km2 to 905 km2 and settlements have increased from 81 km2 to 206 km2 between the years 2000 and 2020. From the chi-square test, it was found a significant association between ecosystem change and biodiversity loss. It was further identified that waterbody decreases have significant impacts on aquatic ecosystems. The results of this study also indicated that due to the introduction of foreign tree species, local and native species have been significantly decreasing over the time. This study emphasizes the non-anthropocentric and inclusive land use policy implications for protecting life on land and preserving the aquatic ecosystem in Bangladesh.
Border cities face significant challenges due to political, environmental, and social issues. Strong urban governance can help resolve many of these problems, but it requires identifying practical factors specific to each city’s location. This study aimed to assess the state of urban governance in Paveh, a border city with a population of 25,771 people. The research used both primary data collection (through a questionnaire) and secondary data sources (local and national databases and documents). The study randomly selected 379 households from Paveh’s population and determined a reliability value of 0.913 using the Cochrane procedure. To assess Paveh’s urban governance, eight criteria were used: participatory, rule-of-law compliance, transparency, responsiveness, consensus-oriented, equitable and inclusive, effective and efficient, and accountability. The findings revealed that Paveh’s urban governance, particularly in the dimensions of transparency and participation, is in an unfavorable situation.
This exploratory study aims to identify the main characteristics and relationships between artificial intelligence (AI) and broadband development in Asia and the Pacific. Broadband networks are the foundation and prerequisite for the development of AI. But what types of broadband networks would be conducive are not adequately discussed so far. Furthermore, in addition to broadband networks, other factors, such as income level, broadband quality, and investment, are expected to influence the uptake of AI in the region. The findings are synthesized into a set of policy recommendations at the end of the article, which highlights the need for regional cooperation through an initiative, such as the Asia-Pacific Information Superhighway (AP-IS).
Poverty, and especially the widening disparity between the rich and the poor, leads to social unrest that can interrupt the harmonious development of human society. Understanding the reasons for income inequality, and supporting the development of an effective strategy to reduce this inequality, have been major goals in socioeconomic research around the world. To identify the determinants of the income gap, we calculated the Gini coefficients for Chinese provinces and performed regression analysis and contribution analysis for heterogeneity, using data from 30 Chinese provinces from 2002 to 2018. We found that urbanization, higher education, and foreign direct investment in eastern China and energy in central and western China were important factors that increased the Gini coefficient (i.e., decreased equality). Therefore, paying more attention to the fair distribution of the factors that can increase the Gini coefficient and investing more in the factors that can reduce the Gini coefficient will be the keys to narrowing the income gap. Our approach revealed factors that should be targeted for solutions both in China and in other developing countries that are facing similar difficulties, although the details will vary among countries and contexts.
The golden visa is a regulation designed to facilitate foreign nationals through a residence permit scheme with an emphasis on investment and citizenship. This research aims to look at the development of the golden visa as an innovation policy, and find out how its implications for the flow of foreign investment into Indonesia. This research uses online research methods (ORM) to discover new facts, information and conditions through technology and internet searches. The aspects used to conduct analysis in this descriptive qualitative research are using innovation policy instruments which include regulatory, economic, financial, and soft instruments. The research findings show that the golden visa as an innovation policy has great potential to support national development through investment in priority sectors. However, its implementation needs to be done carefully with strict supervision and inclusive regulations so as to mitigate risks such as money laundering and property price inflation. That way, golden visas can encourage sustainable and inclusive economic growth through the smooth flow of incoming foreign investment.
Governments intervene in the housing market via implementing various monetary, fiscal, foreign exchange and credit policies. By this, the housing market undergoes cycles of boom and bust as well as significant swings in value added and housing prices. Therefore, the main goal of this research is to consider the effect of the government’s change on the monetary and financial policy’s impact on the business cycles of the housing sector during the period of 1978–2020. On the other hand, we estimate the impact of monetary and fiscal policies on housing business cycles concerning government’s change. To calculate housing business cycles (boom and busts), the housing value added were initially de-trended using the Hodrick–Prescott filter. This paper takes a novel use of the threshold regression model with government’s change as threshold variable. According to the study’s findings, there are three threshold effects (two threshold levels or three regimes) of monetary and fiscal policy on housing business cycles. For instance, the money supply coefficient in the first regime was −1.68, indicating that the effect of monetary policy in this regime is countercyclical. in the second and third regimes, it was 0.19 and 0.03, respectively; indicating its alignment with the housing business cycle. Regarding the estimated models, we may derive several interesting conclusions. In first regime, the money supply is countercyclical and government expenditure is pro-cyclical. This means that monetary policy exacerbates recession and fiscal policy weakens it. in the second and third regimes, the money supply is pro-cyclical and government expenditure is countercyclical. As a result, while formulating their monetary policies, governments should give the housing sector more consideration. Additionally, when putting this policy into practice, the housing sector has to be carefully examined.
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