Impact of high-speed railway construction on spatial patterns of regional economic development along the route: A case study of the Shanghai–Kunming high-speed railway

The Shanghai–Kunming high-speed railway spans the eastern, central, and western regions of China and is an important "horizontal" in the "eight vertical and eight horizontal" railway network of China. This paper estimates the direct impact of opening a high-speed railway on the spatial patterns of regional economic development along the route by integrating GIS technology, spatial panel data models, and the entropy method. The results show that the high-speed railway can significantly increase the economic aggregate and urbanization rates along the route and promote the upgrading of industrial structures, but it has a limited effect on the economic growth rate, showing a weak trend. In terms of spatial patterns, the high-speed railway significantly improves regional accessibility, the strength of economic ties, and economic potential along the route. The regional economy is characterized by weak spatial agglomeration and presents a trend of balanced development. In general, although the economic effect of HSR for the economically lagged regions is smaller in the short term than that in the economically and less economically developed regions, the high-speed railway has the greatest impact on regional economic development and spatial patterns in economically backward areas, thus the economically backward regions have a greater posterior advantage, which is conducive to balancing regional economies and narrowing regional differences.     

The heterogeneous impact of taxation on economic development: New insights from a panel cointegration approach

In this paper, we study the role of taxation on long-run income performance. In the theoretical part of the study, we develop a stylized model based on Barro (1990), in which income taxation has two contradictory roles in the standard Solow (1956) setup: on the one hand, taxation appropriates resources that would otherwise be used for physical capital accumulation, and on the other, it is the source of government spending, which is used to support private production. In the empirical part of the study, the impact of consumption tax, personal income tax, corporate profit tax and property tax on income is estimated using the common correlated effects (CCE) panel cointegration approach, which allows for cross-sectional dependencies and provides both panel- and country-specific results. The panel findings for 30 OECD countries for the period of 1995–2016 indicate that only consumption tax has a statistically significant negative effect on long-run income. However, because the type and sign of the tax coefficients are heterogeneous for the country-specific results, we conclude that taxation has heterogeneous effects on income.     

IFRS,financial development and income inequality: An empirical study using mediation analysis

Income inequality continues to be an issue of concern. Early work on economic development suggested that, as a country’s economy grows, incomes would rise and reduce any income disparities. However, there is growing evidence that as countries develop, income inequality actually worsens. Some studies argue that this is the result of financial development and the growth of the financial sector. Although there is a good deal of empirical research on the relationship between financial development and income inequality, there is no prior work that examines how accounting standards, in particular International Financial Reporting Standards (IFRS), might influence this relationship. This study examines the relationship of IFRS and financial development with income inequality using mediation analysis over the period from 1998 to 2018. The results indicate that the impact of IFRS on income inequality is mediated by financial development. Moreover, there is a direct relationship between IFRS and inequality.     

Impact of high-speed rail on urban economic development: An observation from the Beijing-Guangzhou line based on night-time light images

The high-speed rail (HSR) of China has developed and expanded rapidly and made great achievements in the past twenty years. The ongoing HSR plan is expected to have a significant impact on the urban economy and spatial structure in China. However, relevant data-driven research is still lacking. Traditional data collection approaches such as field surveys are costly to assure the accuracy of materials. In this study, a new remote sensing perspective of night-time light (NTL) was adopted to observe the long-term impact of the HSR on cities along the rail. More specifically, we investigated the impact of the Beijing–Guangzhou High-Speed Railway (BGHSR) on urban economic development by using night-time light data from 2002 to 2018. Such a line connects the capital (located in the north of China) and southern China and lies on the most important geographic axis of the country. Our results find that the construction of BGHSR line has a considerable positive impact on economies of first-tier cities (e.g., Beijing and Guangzhou) and new-first-tier cities (e.g., Zhengzhou, Wuhan, and Changsha), but also hurt some second-tier and third-tier cities such as Baoding and Handan. Generally, the spatial economic pattern of cities along the BGHSR line has been rapidly reshaped with the change of the transportation system. Each city needs to reconsider its role and value in the coming regionalization process to adapt to the national strategy.     

A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: An application for provinces of Iran

Human Development Index (HDI) is a useful tool for policy makers to understand the degree of development in their societies and set new policies to improve it. Traditionally, the United Nations Development Program (UNDP) releases HDI scores of countries based on the three key dimensions of healthy life, population education and standards of living annually. However, HDI scores have some deficiencies such as methodology, indexes selection and measures time lag. In this paper, a new approach is proposed to calculate semi-HDI scores. First, in each dimension of health, education and standard of living, new and extra criteria are selected. Then, policy makers' preferences are considered to assign the weights of criteria in each dimension using best worst method (BWM). Then, MULTIMOORA method is applied to rank provinces of Iran in each dimension. Finally, the semi-HDI scores of provinces are calculated based on geometric mean of healthy life, population education and living standards. According to the semi-HDI scores, Kohgiluyeh & Boyer- Ahmad and Sistan & Baluchestan provinces are the most and the least developed provinces of Iran, respectively.     

Industry convergence as a strategy for achieving sustainable development of agricultural complex: The case of Sandun‐Lanli in China

The purpose of the paper is to conceptualize and provide empirical evidence for the adoption of industry convergence strategy to sustainably develop the agricultural complex (AC) as a form of multifunctional agriculture in the Chinese context, which aims to achieve environmental sustainability in agricultural production and promotion of farmers' income and employment opportunities. A longitudinal single‐case study method was adopted. Thirty‐six face‐to‐face interviews were carried out with key respondents from various levels and types of government agencies, the Wu‐Sheng Company, and village collectives; participative observations were conducted during the fieldwork between 2016 and 2019. We found sustainability is embedded in and achieved through the industry convergence strategies of AC in the rural area of China. We are the first to formally define AC, propose the four‐stage industry convergence strategies of Wu‐Sheng in the process of developing the AC, and build connection between the AC and sustainable development. The case provides important, rich insights into the AC, industry convergence, and agricultural land use policy and therefore has enormous implications for agricultural companies as well as governments.     

Forecasting national activity using lots of international predictors: An application to New Zealand

We assess the marginal predictive content of a large international dataset for forecasting GDP in New Zealand, an archetypal small open economy. We apply “data-rich” factor and shrinkage methods to efficiently handle hundreds of predictor series from many countries. The methods covered are principal components, targeted predictors, weighted principal components, partial least squares, elastic net and ridge regression. We find that exploiting a large international dataset can improve forecasts relative to data-rich approaches based on a large national dataset only, and also relative to more traditional approaches based on small datasets. This is in spite of New Zealand’s business and consumer confidence and expectations data capturing a substantial proportion of the predictive information in the international data. The largest forecasting accuracy gains from including international predictors are at longer forecast horizons. The forecasting performance achievable with the data-rich methods differs widely, with shrinkage methods and partial least squares performing best in handling the international data.     

The effect of ownership on sustainable development and environmental policy in urban waste management: An explicatory empirical analysis of Italian municipal corporations

This paper investigates the effect of ownership on sustainable development and environmental policy in Italian municipally owned corporations (MOCs) dealing with urban waste management, trying to understand if multiple ownership can generate better performance compared to single ownership and if the presence of private partners could be crucial in this. The research question is answered by analyzing 41 MOCs of the largest Italian cities operating in urban waste management. In this specific sector, public administrations have tried to improve their offer in terms of sustainable development, environmental policy, and efficiency. The paper covers the Italian case study, where urban waste production per capita is higher than the European average figure. The waste cycle management service is operated in Italy at local level through totally publicly owned companies (monoadministration or multiadministration), mixed (public–private) companies, or via a full externalization achieved by means of public tenders. Through a multinomial ordered probit panel, we show that MOCs with multiple owners perform better than those having a single owner and perform much better with the presence of a private partner, confirming those academic findings according to which collaborative arrangements can increase efficiency, do better than public sector bureaucracy, and lower the costs of service provision. The results of this paper can be used by academics, practitioners, and policy makers alike. To the best of our knowledge, this is the only study that applies this perspective to the analysis of the current international waste management scenario with relation to MOCs having multiple ownerships.     

Strategic business risk evaluation for sustainable energy investment and stakeholder engagement: A proposal for energy policy development in the Middle East through Khalifa funding and land subsidies

This article projects business risk through deferent industrial scenarios in concentrated solar investments in the United Arab Emirates (UAE). Nationwide, the government seeks a sustainable solution through energy policy development and engagement of the stakeholders for clean energy generation at wider level in the long run. Support has been extended through various support schemes. In the current study, Monte Carlo simulations and net present value (NPV) risk are used to analyse the return on investment. A 5 MW concave solar panel project is evaluated. We have assessed the impact of local factors on profits through NPV. The study proposes that a higher NPV is expected if the concave solar panel project is financed 50% by Khalifa funding. The study also proposes a robust policy and highlights the opportunity of business profitability if the government subsidises land leasing with respect to each scenario. Additionally, the study also proposes a policy to maintain the interests of investors in the UAE.