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What is the relation between the land system with Chinese characteristics and the country's high-speed economic growth in the past decades? There is a lack of rigorous academic research based on the general equilibrium theory of macroeconomics on this issue.

By building a multisector dynamic general equilibrium framework with land system, this paper explores how the land supply mode with Chinese characteristics affects China's economic growth as well as its transmission mechanism.

This paper confirms the importance of land system with Chinese characteristics in explaining the mystery of China's high-speed economic growth. Counterfactual analysis shows that if China adopts a land system similar to that of other developing countries, GDP will drop 36% from the current level under the baseline model.

As the industrial sector shrinks relatively and the output elasticity of infrastructure decreases, this inhibitory effect will become more apparent. China should improve its land supply mode, especially expand the supply of commercial and residential land and reduce the cost of land in the service sector. This can promote better economic development in the future and thus improve household welfare and the structure of aggregate demand, replace “land-based public finance” and thus inhibit the “high leverage” risks of local governments.

This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

At present, China’s industrial spatial layout faces the predicament of over-agglomeration of Eastern China industries and the near disintegration of industrial structure in the central and western regions. The paper aims to discuss this issue.

Based on the perspective of differentiated inter-regional labor mobility, this paper constructed a model framework of quadratic sub-utility quasi-linear preference utility function, and conducted model deduction and numerical simulation on causal factors of this spatial imbalance along the two dimensions of individual and regional welfare.

The study finds that in the long run, industrial spatial layout imposes a certain threshold limit on the portfolio proportion of differentiated labor. The dilemma of China’s industrial spatial layout is attributable to the deviation of the market’s optimal agglomeration from the social optimal agglomeration, and to the disfunction of Eastern China’s role as an intermediary between the global and the domestic value chain.

To resolve this predicament of industrial layout, the unitary welfare compensation based on fiscal transfer payment has to be switched to a more comprehensive approach giving consideration to industrial rebalancing.

Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors.

Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors.

The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative.

This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.

The purpose of this paper is to systematically review the evolution, characteristics, motivations, entry patterns, organizational structure and effectiveness of the internationalization of Chinese research institutions in the past 40 years of reform and opening-up.

This paper describes the evolution and practice of Chinese research institutions “going out” by constructing a theoretical framework diagram and uses official statistics and existing research to explain the authors’ points.

The research results show that the internationalization of research institutions has undergone four phases: sprout period, starting period, adjustment period and accelerating period. It shows a rapid growth of investment scale, diversification of investment entities, rich and varied forms, and transition to major countries along the “One Belt and One Road.” Expanding the international market, tracking and acquiring technological frontiers, nurturing domestic R&D talents, and evading the risks of political, economic, cultural and scientific differences between home and host countries are the main motivations for Chinese research institutions to “go global.” Multinational corporations have entered the host country with modes such as M&A, greenfield investment and joint R&D alliances in their own strengths and also presented a variety of organizational structures such as integrated R&D networks.

This paper systematically summarizes the internationalized experience model of research institutions with Chinese characteristics since the reform and opening-up. From the perspective of internationalization model transformation, policy integration and cooperation among emerging economies, it presents the opportunities and challenges faced by the research institutions in the process of internationalization and provides a theoretical basis for improving the internationalization ability of research institutions.

This study focuses on forecasting the price of the most important export crops of vegetables and fruits in Egypt from 2016 to 2030.

The study applied generalized autoregressive conditional heteroskedasticity (GARCH) model and autoregressive integrated moving average (ARIMA) model.

The results show that ARIMA (1,1,1), ARIMA (2.1,2), ARIMA (1,1,0), ARIMA (1,1,2), ARIMA (0,1,0) and ARIMA (1,1,1) are the most appropriate fitted models to evaluate the volatility of price of green beans, tomatoes, onions, oranges, grapes and strawberries, respectively. The results also revealed the presence of ARCH effect only in the case of Potatoes, hence it is suggested that the GARCH approach be used instead. The GARCH (1,1) is found to be a better model in forecasting price of potatoes.

The study of food price volatility in developing countries is essential, since a significant share of household budgets is spent on food in these economies, so forecasting agricultural prices is a substantial requirement for drawing up many economic plans in the fields of agricultural production, consumption, marketing and trade.

The purpose of this paper is to provide a theoretically rigorous and practically relevant summary of research findings that enables managers to drive sustainable profits improvements via pricing. It showcases multiple case studies that demonstrate how companies can achieve higher-than-average profitability by implementing intelligent pricing strategies and tactics.

Over the past 20 years, this writer has conducted dozens of academic surveys with managers exploring the antecedents, moderators and consequences of pricing practices for existing and new products. The writer has analyzed all pricing research published in leading academic journals over the past decades. Finally, as equity partner of Hinterhuber & Partners, a pricing consultancy (www.hinterhuber.com), this writer – through collaborations with companies and workshops conducted with practicing managers – has collected data and insights on best practices in managing pricing as a strategic activity.

Pricing is the most powerful driver of superior profits, yet managers view pricing as relevant only in the context of innovation. This narrow view prevents companies from realizing their full potential. Best practice examples of pricing as well as rigorous academic research suggest that pricing based on solid scientific principles helps average companies to achieve above-average results. This paper presents a review of recent research and summarizes the fundamental principles that managers must master so that pricing becomes an enabler of lasting superior performance.

Academic research in pricing surpasses managerial practice. Managers often rely on outdated concepts when it comes to pricing strategy and tactics.

The paper presents a framework that allows managers to implement pricing strategies that improve performance.

Effective pricing strategies benefit companies, customers and other stakeholders.

The paper provides a comprehensive overview of the latest research on pricing and thus documents that pricing based on solid, scientific principles is an enable of lasting, above-average profitability.