Analysis and Prediction of Expansion of Central Cities Based on Nighttime Light Data in Hunan Province, China

Quantifying the characteristics of urban expansion as well as influencing factors is essential for the simulation and prediction of urban expansion. In this study, we extracted the built-up regions of 14 central cities in the Hunan province using the DMSP-OLS night light remote sensing datasets from 1992 to 2018, and evaluated the spatial and temporal characteristics of the built-up regions in terms of the area, expansion speed, and main expansion direction. The backpropagation (BP) neural network and autoregressive integrated moving average (ARIMA) model were used to predict the area of the built-up regions from 2019 to 2026. The model predictions were based on the GDP, ratio of the secondary industry output to the GDP, ratio of the tertiary industry output to the GDP, year-end urban population, and urban road area. The results demonstrated that the built-up area and expansion speed of the central cities in the eastern part of the Hunan province were significantly higher than those in the western part. The main expansion directions of the 14 central cities were east and south. The urban road area, year-end urban population, and GDP were the main driving factors of the expansion. The urban expansion model based on the BP neural network provided a high prediction accuracy (R = 0.966). It was estimated that the total area of urban built-up regions in the Hunan province will reach 2463.80 km2 by 2026. These findings provide a new perspective for predicting urban areas rapidly and simply, and it also provides a useful reference for studying the spatial expansion characteristics of central cities and formulating a sustainable urban development strategy during the 14th Five-Year Plan of China.

A study on the spatial and temporal evolution of urban shrinkage and its influencing factors from a multidimensional perspective: A case study of resource-based cities in China

With social and economic environment changes occurring in the world and deepening of the urbanization process, China’s urban development exhibits a new phenomenon of growth and shrinkage fluctuations. The resource-based city shrinkage phenomenon is particularly prominent. Research on the commonalities and patterns of similar groups should be enhanced. We constructed an urban shrinkage evaluation index system from the three dimensions of population, economy and space. Accordingly, we explored the spatiotemporal evolution characteristics of 175 resource-based cities in China from a multidimensional perspective with the entropy method, shrinkage model and transfer matrix method. The results indicated that most resource-based cities in China occurred in the non-shrinking state, but their development speed gradually decreased or even presented stagflation. The shrinkage measure-related results in the different dimensions revealed that the number of shrinking cities is increasing. The population, economic and comprehensive shrinkage levels were mainly slight and remained stable. The number of cities experiencing moderate and severe shrinkage was relatively small and mostly encompassed short-term shrinkage. Spatial shrinkage demonstrated a clear administrative hierarchy difference. Moreover, the spatial distribution range of shrinking cities in each dimension expanded and exhibited obviously similar characteristics, i.e., shrinking cities were relatively concentrated in Northeast China, while they were more scattered in other regions. Furthermore, the geodetector technique was applied to reveal the influencing factors of resource-based city growth and shrinkage. Based on the results, the change in the secondary industry output value share at the start of the study was the primary factor. The impact of each employment structure indicator from 2014 to 2018 was particularly significant. Comprehensive exploration of the shrinkage characteristics of this particular group of cities and their development behavior from a multidimensional perspective can provide an important reference for the transformation and high-quality development of resource-based cities.

COVID-19 impact study: assessing the consequences of the pandemic on economic output in developing countries for targeted sectors

This paper presents a model for how the impact of the COVID-19 pandemic on economic output in developing countries can be assessed with a new approach. Existing models lack sectoral granularity in developing countries, which can, however, be obtained through input-output modelling by changing the social accounting matrix to simulate a COVID-19 economy. Results have been estimated for 65 sectors and 141 regions which correspond to the Global Trade Analysis Project’s data. The analyses showed that the average impact in Africa and Asia on industry output is −2.6 per cent and −2.9 per cent, respectively. It is estimated that tourism and services are the most heavily impacted sectors, between −15 per cent and −19 per cent for hospitality, recreation, and other service activities, and between −4 per cent and −7 per cent for transport services. The model is a first attempt at estimating impact at this level of granularity per country and sector, which by triangulation with empirical data can be used to make substantiated management or policy decisions.

Labour Market Flexibility in the Context of the Shadow Economy for the Construction Industry

The article analyses labour market flexibility in the context of the shadow economy. The main research problem is devoted to the flexibility of the construction labour market in relation to the level of labourers who work in a country's shadow economy. The following hypothesis was adopted: Flexibility of the labour market for the construction industry decreases with an increase in the level of the shadow economy. The MIMIC approach was used to calculate the level of the shadow economy in a group of selected countries, divided into three categories. The first category includes countries with a relatively low level of shadow economy (less than 15% of their GDP). The second group contains a level starting from 15 to 25% of their GDP, while the third group has a shadow economy that exceeds 25% of GDP. The Pearson correlation index was applied in order to measure the coefficient level between market flexibility and the size of the shadow economy. The flexibility of the labour market was calculated as the change of unemployment caused by the change of construction industry output. The research proved that the correlation between market flexibility and the shadow economy is significant. This is due to the fact that the Pearson index reached the level of 0.866, which means that whenever the shadow economy increases, the labour market flexibility of the construction industry decreases. (original abstract)

Light industry during the years of the Kosygin reform (1965–1970): analysis of the growth rates of the total volume of light industry output based on reference books on Soviet industry and Consolidated reports of the Central Statistical Administration of the USSR Council of Ministers

The article represents indices of the Soviet Union’s light industry, such as gross output, rate of growth of gross output during the eighth five-year plan. The data for statistical analysis were taken from industrial reference books and the Central Statistical Administration of the Council of Ministers of the USSR’s archive fund. Problem of the research is disparity of same indices in different sources. During a statistical analysis arithmetical mean was count for each analysed index, and it was discovered which source’s data were the closest to the means.

Economic Contributions of the Green Industry in the United States in 20181

The economic contributions of the green industry in the United States were estimated for 2018 using information on industry employment and wages, and economic multipliers from a U.S. IMPLAN economic model. Direct industry output for all sectors was estimated at $159.57 billion (B), and total output contributions, including indirect and induced regional economic multiplier effects of export sales, were $348.08 B. The total value added contribution to the Gross Domestic Product (GDP) was $190.98 B, including labor income contributions of $121.55 B, other property income contributions of $16.01 B and business taxes paid to local, state and federal governments of $25.84 B. The industry had direct employment of 1,599,662 fulltime and part-time individuals, and total employment contributions of 2,315,357 jobs in the broader economy. The largest individual industry sectors in terms of employment and GDP contributions were landscaping and horticultural services (1,460,669 jobs, $221.89 B), greenhouse, nursery and floriculture production (217,574 jobs, $28.69 B), and lawn and garden equipment and supplies stores (292,614 jobs, $43.80 B). The top ten states in terms of employment contributions were California (264,913 jobs), Florida (203,482), Texas (161,151), Ohio (90,406), Pennsylvania (90,075), New York (90,266), Illinois (87,595), North Carolina (78,766), Michigan (77,719), and Georgia (66,527). Since 2013, green industry contributions in 2018 increased by 16.2% for employment and 17.3% for GDP in inflation-adjusted terms. Growth in the industry was highest for wholesale and retail trade, while production and manufacturing declined. Although the green industry has grown slowly in recent years, it remains an important contributor to national, state and local economies. Index words: Sales, industry output, employment, value added, Gross Domestic Product, production, manufacturing, landscaping services, wholesale, retail, lawn and garden product line.

Influence of Interest Rate on Industrial Output in Nigeria

The study examined the effect of interest rate on industrial sector in Nigeria from 1980 to 2018. The data for the study were sourced from Central Bank of Nigeria (CBN) statistical bulletin and Autoregressive Distributed Lag model was used as the main analytical tool. The ARDL Bounds test revealed the existence of long run relationship among the variables. The result further revealed the existence of a positive relationship between interest rate and industrial output both in the long run and short run. The rate of inflation was negatively related to industrial output but the relationship was not significant in both the short run and the long run. The number of labour force affected the productivity of industry thereby increasing its output in both the short run and the long run. Gross investment has a positive relationship with industrial output but the relationship was not significant. Lastly, foreign direct investment was not significant in affecting industrial output in the short run but it was positive and significant in affecting industrial output in the long run. The study concluded that interest rate has the ability to influence industry output in Nigeria. Therefore, the study recommended among others that the apex monetary institution - the Central Bank of Nigeria should ensure that the rate of interest that will encourage investors to borrow in order to start to do businesses or to expand their businesses. This will increase industry output and in turn support economic growth in Nigeria.

Problems and Peculiarities of the Light Industry Development in Ukraine: A Statistical Comparison with EU Countries

The light industry is one of the basic strategic segments of the national economy, providing for 5.0% of budget revenues and 2.6% of Ukrainian merchandise exports, and, therefore, has a considerable potential for further development. The purpose of the article is to identify problems and peculiarities of the light industry development in Ukraine on the basis of a statistical comparison with EU countries. According to the research results, the systemic negative dynamics of the light industry output resulted in a lag between Ukraine and EU countries, e. g. 6 times from Poland, 21 times from Germany, and 73 times from Italy. The light industry in Ukraine (like in the leading EU countries) specializes in manufacturing of final consumption products, which share in the output is more than 60%. However, despite such specialization, nearly 90% of the domestic demand for the light industry goods is met by imports. At the same time, the significant export orientation of textile and other light industry industries given that all the production and consumption segments of these industries in Ukraine have a strong import dependence indicates a high share of tolling operations in the Ukrainian exports. The development of the Ukrainian light industry is hampered by the following key problems: high dependence on imported raw materials, supplies and components; low price competitiveness of home-made goods on the domestic market; the reliance of a large part of domestic companies in the industry on consumer-supplied raw materials. Hence, the priority of the government’s industrial policy for the light industry development is to restore (and further increase) raw materials supplies for textile and other domestic industries. The second objective is to create competitive conditions on the domestic market for the light industry by eliminating the shadow turnover in this segment. The third objective is to reduce the commodity exports, along with increasing exports of high quality products with a high share of value added.

Acid Concentration: A Pre-requisite to Enhanced Metal Dissolution?

Technological advancement over the past decade has dramatically changed with new players such as China taking lead in information-technology and telecommunication market across the world. This development has seen surge in manufacturing industry output and consequently raw materials consumed by the sector. The environmental impact is however evident due to human interference with nature. E-waste is the fastest growing waste stream posing serious risk to fauna and flora due to numerous associated pollutants. In recycling industry, hydrometallurgy is widely adopted to recover metals from e-waste. Despite growing concern over secondary pollution associated with disposal, concentrated aqua regia is widely used to extract metals from e-waste. An ultrasonic bath enhanced dilute-acid leaching method was developed to recover copper and lead from waste mobile phone PCB. Repeatability and reproducibility showed 5.3% and 5.0% with respect to Cu while 9.8% and 6.3% RSD were recorded for lead. LOD and LOQ of 0.02 µg/g and 0.064 µg/g (Cu) and 0.082 µg/g and 0.312 µg/g (Pb) revealed that the method is suitable for dissolution of target metals from PCBs. Copper concentration of 332.98 mg/g recorded inferred that dilute aqua regia as much as concentrated has promising metal extraction power and thus could replace concentrated acids.