Cut Zulfa Husna, Andrea Emma Pravitasari, Andi Syah Putra
Aceh Province has significant regional disparities, especially in the Southwest (Barsela). However, this region is strategically located, prompting the government to develop a strategic area that is the Barsela Special Economic Zone (SEZ) in Southwest Aceh Regency, which is located in Babahrot District, with Kuala Batee District as the closest hinterland. These two districts have the highest poverty rates in the regency, making the SEZ a potential catalyst for new growth center. This study aims to determine priority villages as new growth centers and regional development strategies using scalogram, gravity, network analysis, AHP-TOPSIS, and SWOT methods. Scalogram analysis shows that most villages around the Barsela SEZ have low regional development, with 54% in Hierarchy III, 29% in Hierarchy II, and 17% in Hierarchy I. Gravity analysis indicates low to moderate regional interactions, with NTIAD below 4,000,000 interaction units. Road network centrality is also generally low, with only four villages classified as high, based on Degree Centrality (0.31), Closeness Centrality (0.26), and Betweenness Centrality (0.43). Based on AHP-TOPSIS, Pante Rakyat Village is prioritized as a new growth center due to its high regional development, strong attractiveness, and good spatial centrality. The main development strategy is the Turnaround Strategy, which focuses on utilizing opportunities and addressing weaknesses. This research is expected to support spatial planning around the Barsela SEZ and contribute to Southwest Aceh Regency and Aceh Province government policies.
Unlike existing studies that concentrate on haze pollution at the provincial and city levels in China, this study utilizes data from 1762 counties from 2009 to 2020. Using a multi-temporal difference-in-differences method, the study investigates the impact of green finance reform and innovation pilot zones (GFRIs) on county haze pollution (CHP) through the synergy of governmental departments and financial institutions. The findings indicate that GFRIs can reduce CHP, and this effect is realized by promoting green innovation, strengthening environmental penalties, and alleviating fiscal pressure. Heterogeneity analysis demonstrates that the inhibitory effect of GFRIs on CHP is more pronounced in counties with lower levels of financial development, higher levels of industrial development, poorer and in the central and western regions. The GFRIs achieve a win-win situation for economic growth and pollution reduction. The GFRIs should leverage the synergy of “active” government and “effective” market, establishing a long-term mechanism for CHP control.
Economic growth, development, planning, Economic history and conditions
Pruning is an essential agricultural practice for orchards. Proper pruning can promote healthier growth and optimize fruit production throughout the orchard's lifespan. Robot manipulators have been developed as an automated solution for this repetitive task, which typically requires seasonal labor with specialized skills. While previous research has primarily focused on the challenges of perception, the complexities of manipulation are often overlooked. These challenges involve planning and control in both joint and Cartesian spaces to guide the end-effector through intricate, obstructive branches. Our work addresses the behavior planning challenge for a robotic pruning system, which entails a multi-level planning problem in environments with complex collisions. In this paper, we formulate the planning problem for a high-dimensional robotic arm in a pruning scenario, investigate the system's intrinsic redundancies, and propose a comprehensive pruning workflow that integrates perception, modeling, and holistic planning. In our experiments, we demonstrate that more comprehensive planning methods can significantly enhance the performance of the robotic manipulator. Finally, we implement the proposed workflow on a real-world robot. As a result, this work complements previous efforts on robotic pruning and motivates future research and development in planning for pruning applications.
Abstract The amount of electricity generation and its availability to the residents of a country reflects its level of development and economic condition. Water being one of the cheapest and renewable sources of energy, is being used to produce one-quarter of the total electricity production in Pakistan. This article presents a forecasting study of hydroelectricity consumption in Pakistan based on the historical data of past 53 years using Auto-Regressive Integrated Moving-Average (ARIMA) modeling. Based on the developed forecasting equation, the hydroelectricity consumption was predicted up to the year 2030. For validating the reliability of the forecasted data, the results were compared to the actual values which showed good fit with minimum deviation. The forecasted values of hydroelectricity consumption revealed an average annual increment of 1.65% with a cumulative increase of 23.4% up to the year 2030. The results were compared with the hydroelectricity generation plans of the Government of Pakistan for its effectiveness. A sensitivity analysis was also performed to study the relation of hydroelectricity consumption to the annual population and GDP growth rate of the country. The research shall significantly prove to be useful in better planning and management of water resources of Pakistan for future.
This research evaluates the long-term asymmetric impacts of insecurity and corruption on the development of tourism in Nigeria using a non-linear ARDL (NARDL) method to analyze quarterly data for the 1996-2021 period. The cointegration test result provides an evidence of a long-term relationship among these three variables (corruption, insecurity and tourism development), along with exchange rate, income and infrastructure. The asymmetry test results reveal asymmetry between tourism development and both corruption and insecurity. The outcomes of the empirical exercise indicate that a positive shock to control of corruption (decline in corruption) fosters long-term tourism development, while a negative shock to control of corruption (increase in corruption) does not significantly explain long-term tourism development. In addition, a positive change in government expenditure on internal security (increase in internal insecurity) lowers long-term tourism development, but a negative change in government spending on internal security (decrease in internal insecurity) enhances long-term tourism development. Depreciation of the domestic currency promotes long-term tourism development. Thus, policies that reduce corruption and insecurity are recommended to promote long-term development of the tourism sector in Nigeria.
Nugroho Agung Pambudi, Windah Yuniar, Desita Kamila Ulfa
et al.
The transition to renewable energy is hindered by the level of acceptance in society. The role of education in schools is crucial, and while numerous studies have been conducted, there is still a lack of exploration into the depth of the materials. This research was carried out to assess the readability level of material on renewable energy from geothermal resources in Vocational High School textbooks. The descriptive quantitative method was used, conducted in 19 Vocational High School with a study program in Technology and Engineering in Surakarta. The sample size was 340 respondents. Data were collected from textbooks and questionnaire results. The Gunning Fog Index scores indicated the material had low readability level with scores of 20, 18, and 21 for texts 1, 2, and 3. Text 1 is taken from book titled 'Energy Conversion Machines', Text 2 from 'Sustainable Energy Saving through Building', and Text 3 from 'Basic Knowledge of Mechanical Engineering. Additionally, the responses of readers indicated that more than 50% of respondents could easily comprehend the content in texts 2 and 3. Resulting, for text 1, over 50% of respondents reported understanding the content with some difficulty. These three books are also commonly used, making this research a valuable recommendation for stakeholders in curriculum design and educational planning.
Viriyasack Sisouphanthong, Latdaphone Banchongphanith, Sthabandith Insisienmay
et al.
The Association of Southeast Asian Nations (ASEAN) has emerged as one of the fastest growing collective economies in Asia. This fast growth is, however, accompanied by various challenges, including the trade-related illicit financial flows (IFFs) that deplete the tax revenues of the Association’s Member States. This chapter aims to shed light on the status of the trade-related IFFs present in the scale of trade mispricing that occurs between the ASEAN community and its global trade partners. To better interpret its findings, the chapter provides a legal framework analysis that highlights gaps in efforts to address these financial challenges in the region. Notwithstanding these gaps, certain Member States with substantial non-tax revenue streams have reduced reliance on conventional taxation, allowing for unique fiscal strategies. A comparative analysis of readiness among ASEAN Member States, meanwhile, reveals disparities, with advanced economies demonstrating robust legal systems while developing countries face challenges in implementing complex tax regulation. The chapter also examines the vulnerability of countries that lack robust legal frameworks, using the Lao People’s Democratic Republic (PDR), a landlocked, least-developed country dependent on extractive resources and agricultural exports, as a case study. By estimating the magnitude of trade mispricing of selected mineral and agricultural product exports, the chapter tries to present the consequential impact on potential tax revenue erosion and the economy. Its findings underscore the critical role of legal foundations in addressing the issue of IFFs, including the importance of transfer pricing rules in preventing trade mispricing. Based on these findings, this study encourages less economically developed, tax-revenue-reliant nations like Lao PDR to continue developing a transparent legal system, improve current trade databases, and enhance cooperation with international bodies. This study also suggests such countries explore alternative methods, such as simplified approaches, of estimating tax liabilities and curbing trade mispricing.
Political science, Economic growth, development, planning
We consider a class of economic growth models that includes the classical Ramsey--Cass--Koopmans capital accumulation model and verify that, under several assumptions, the value function of the model is the unique viscosity solution to the Hamilton--Jacobi--Bellman equation. Moreover, we discuss a solution method for these models using differential inclusion, where the subdifferential of the value function plays an important role. Next, we present an assumption under which the value function is a classical solution to the Hamilton--Jacobi--Bellman equation, and show that many economic models satisfy this assumption. In particular, our result still holds in an economic growth model in which the government takes a non-smooth Keynesian policy rule.
In this chapter, an input-output economic model with multiple interactive economic systems is considered. The model captures the multi-dimensional nature of the economic sectors or industries in each economic system, the interdependencies among industries within an economic system and across different economic systems, and the influence of demand. To determine the equilibrium price structure of the model, a matrix-weighted updating algorithm is proposed. The equilibrium price structure is proved to be globally asymptotically achieved when certain joint conditions on the matrix-weighted graph and the input-output matrices are satisfied. The theoretical results are then supported by numerical simulations.
We use generative AI to extract managerial expectations about their economic outlook from 120,000+ corporate conference call transcripts. The resulting AI Economy Score predicts GDP growth, production, and employment up to 10 quarters ahead, beyond existing measures like survey forecasts. Moreover, industry and firm-level measures provide valuable information about sector-specific and individual firm activities. A composite measure that integrates managerial expectations about firm, industry, and macroeconomic conditions further significantly improves the forecasting power and predictive horizon of national and sectoral growth. Our findings show managerial expectations offer unique insights into economic activity, with implications for both macroeconomic and microeconomic decision-making.
This paper explores the features of cyclonic disturbances (CDs) in the North Indian Ocean (NIO) by utilizing data from 1990 to 2022. It investigates the occurrence rate of these disturbances and their effects on human and economic losses throughout the mentioned period. The analysis demonstrates a rising trend in the occurrence of CDs in the NIO. While there has been a slight decline in CD-related fatalities since 2015, but there has been a considerable increase in economic losses. These findings can be attributed to enhanced government initiatives in disaster prevention and mitigation in recent years, as well as rapid economic growth in regions prone to CDs. The study sheds light on the significance of addressing the impact of CDs on both human lives and economic stability in the NIO region.
Abstract Carbon emissions and energy consumption have serious impacts on humans and ecosystems. This paper investigates the effects of industrial reconstructuring on energy conservation and emission reduction. A multi-objective optimization model was established. The model classifies industrial sectors into four groups according to their carbon emission levels and contributions to economic growth, then non dominated sorting genetic algorithm is applied to solve the model and the Pareto frontier is obtained. The best solution is selected from the Pareto frontier by using a super data envelopment analysis model which measures the degree of coordination between economy and environment. The model is used to analyze the effects of industrial reconstructuring in Beijing during 2018–2020. The results show that industrial reconstructuring enabled economic growth to reach the government’s planned rate while the carbon intensity and energy intensity surpassed the goal of the 13th Five-Year Plan. This case can provide decision-making basis for the sustainable development of ecology and economy in other regions.
The level of development of the aviation industry is an indicator of the scientific and technical potential of any state and also affects its economic level. This industry practically cannot exist without interaction with other countries, as technical achievements, scientific discoveries, know-how of some countries help other countries to develop the aircraft industry, as well as bring it to a new level. Manufacturers of civil aircraft interact with a large number of suppliers around the world in order to create a quality product. Using the example of Boeing-industry leader, while studying the role of suppliers and the company’s supply chain, the peculiarities of fragmentation of this company and its positive impact not only on the company’s position in the market inside and outside the country, but also on the development of the entire industry as a whole are shown.
Economic growth, development, planning, Economics as a science
Human mind is the palace of curious questions that seek answers. Computational resolution of this challenge is possible through Natural Language Processing techniques. Statistical techniques like machine learning and deep learning require a lot of data to train and despite that they fail to tap into the nuances of language. Such systems usually perform best on close-domain datasets. We have proposed development of a rule-based open-domain question-answering system which is capable of answering questions of any domain from a corresponding context passage. We have used 1000 questions from SQuAD 2.0 dataset for testing the developed system and it gives satisfactory results. In this paper, we have described the structure of the developed system and have analyzed the performance.
El artículo explora la influencia de las preocupaciones por la deforestación de la Amazonía en la política del cultivo de palma aceitera en el Perú. Para ello se analizaron los discursos subyacentes a la política y de los actores relacionados. Los resultados señalan un cambio de paradigma influenciado indirectamente por las preocupaciones señaladas. Dicha influencia ocurrió presumiblemente mediante los palmicultores, quienes lideraron el reciente proceso de actualización de la política promoviendo su inserción a mercados verdes. También se identificó la necesidad ineludible de incorporar a las comunidades indígenas en la política del cultivo y otras políticas en la Amazonía peruana.
An efficient algorithm is required to extract moving objects (asteroids, satellites, and space debris) from enormous data with advances in observational instruments. We have developed an algorithm, tracee, to swiftly detect points aligned as a line segment from a three-dimensional space. The algorithm consists of two steps; First, construct a k-nearest neighbor graph of given points, and then extract colinear line segments by grouping. The proposed algorithm is robust against distractors and works properly even when line segments are crossed. While the algorithm is originally developed for moving object detection, it can be used for other purposes.
Economic development positions human as an important factor of production. Therefore quality human resources are needed for sustainable development. Indonesia as a country with a large population potential is expected to take advantage of the opportunity through demographic bonuses that will occur in 2020-2030. However, the emergence of NEET (not in employment, education or training) has become a new problem that threatens the success of development. NEET is a measure that includes young people in the age range of 15-24 years old, who are not in employment, education or training. NEET is considered more comprehensive than unemployment because it can see the dynamics and activeness of youth in the labor market. The presence of NEET is inseparable from the determinant characteristics the chances of someone becoming a NEET youth. This study uses Sakernas data for 2017 and 2018 to see the phenomenon and determinant characteristics of NEET status. The result showed NEET youth in West Sumatera was dominated by economically inactive youth. And by using logistic regression analysis, obtained several characteristic that significantly influence the chance of youth’s vulnerability to become a NEET. Youth who live in rural areas have a greater opportunity to become NEET youth, while youth with high level education are even more vulnerable to becoming NEET. Gender does not have a significant effect on determinants of NEET status in areas that adhere to this matrilineal kinship system. Based on the result of this study, the government as the holder of authority is expected to implement policies to reduce the proportion of NEET youth.
The coronavirus disease (COVID-19) has caused one of the most serious social and economic losses to countries around the world since the Spanish influenza pandemic of 1918 (during World War I). It has resulted in enormous economic as well as social costs, such as increased deaths from the spread of infection in a region. This is because public regulations imposed by national and local governments to deter the spread of infection inevitably involves a deliberate suppression of the level of economic activity. Given this trade-off between economic activity and epidemic prevention, governments should execute public interventions to minimize social and economic losses from the pandemic. A major problem regarding the resultant economic losses is that it unequally impacts certain strata of the society. This raises an important question on how such economic losses should be shared equally across the society. At the same time, there is some antipathy towards economic compensation by means of public debt, which is likely to increase economic burden in the future. However, as Paul Samuelson once argued, much of the burden, whether due to public debt or otherwise, can only be borne by the present generation, and not by future generations.
We estimate the relationship between GDP per capita growth and the growth rate of the national savings rate using a panel of 130 countries over the period 1960-2017. We find that GDP per capita growth increases (decreases) the growth rate of the national savings rate in poor countries (rich countries), and a higher credit-to-GDP ratio decreases the national savings rate as well as the income elasticity of the national savings rate. We develop a model with a credit constraint to explain the growth-saving relationship by the saving behavior of entrepreneurs at both the intensive and extensive margins. We further present supporting evidence for our theoretical findings by utilizing cross-country time series data of the number of new businesses registered and the corporate savings rate.