Optimal allocation of direct and embodied arable land associated to urban economy: Understanding the options deriving from economic globalization

Land resources do not flow directly but can be allocated as “embodied land” in goods and services during economic globalization. The term “embodied arable land” can help link local land allocation strategies to the global and national supply chains and trade activities, and suggest new lens in optimizing arable land allocation. China is facing a serious arable land shortage, especially in municipal administrative areas. Based on the nested input-output analysis (Nested IOA), this work takes Shanghai as an example, exploring the allocation of direct and embodied arable land of an urban economy within the process of economic globalization. The amount of embodied arable land associated with Shanghai economy is 6.09 Mha, broken down into local arable land use (0.20 Mha), domestic inflows (3.20 Mha) and foreign inflows (2.69 Mha). This area supports local final demand (4.32 Mha), domestic outflows (1.24 Mha) and foreign outflows (0.53 Mha). Land-related imbalances emerge in the study, namely the economy’s demand versus the city’s size, the arable land demand versus supply, and embodied arable land inflows versus outflows. Regarding the role of the urban economy in allocation of global arable land under economic globalization, on the one hand, Shanghai has intensively involved with a large amount of embodied foreign arable land resources, and has been heavy dependent on foreign embodied arable land; On the other hand, there is still large potential for Shanghai to take the opportunity of economic globalization for an optimal allocation of direct and embodied arable land. Policy suggestions on taking the opportunity of economic globalization for an optimal allocation of direct and embodied arable land are put forward.     

Does the spatial representation affect criteria weights in environmental decision-making? Insights from a behavioral experiment

The need and interest to consider cognitive and motivational biases has been recognized in different disciplines (e.g. economics, decision theory, risk analysis) and has recently reached environmental decision-making. Within this domain, the intrinsic presence of a spatial dimension of both alternatives and criteria calls for the use of maps throughout the decision-making process to properly represent the spatial distribution of the features under analysis. This makes spatial Multi Criteria Decision Analysis (MCDA) a particularly interesting domain to explore new dimensions of cognitive biases. This study proposes a behavioral experiment aimed at discovering to what extent the spatial visualization (i.e. maps) of criteria versus the non-spatial one (i.e. tables) can bias the weight elicitation phase of a spatial MCDA process. The experiment simulates a very common analysis in environmental and land use planning: land suitability analysis. Our findings show that there are significant consequences on how important we perceive a certain criterion to be, depending on whether it is represented as a map or as a table among a mix of maps and tables. Indeed, the map representation of the same criterion leads to higher weights attributed to that criterion compared to the table representation. Visualizing the same information as a map or as a table, although technically equivalent, is thus not psychologically equivalent for Decision Makers. The results of this experiment are expected to have implications for spatial decision-making processes, by generating better awareness on the impacts of map-mediated land suitability analysis.     

High-frequency credit spread information and macroeconomic forecast revision

We examine whether professional forecasters incorporate high-frequency information about credit conditions when revising their economic forecasts. Using a mixed data sampling regression approach, we find that daily credit spreads have significant predictive ability for monthly forecast revisions of output growth, at both the aggregate and individual forecast levels. The relationships are shown to be notably strong during ‘bad’ economic conditions, which suggests that forecasters anticipate more pronounced effects of credit tightening during economic downturns, indicating an amplification effect of financial developments on macroeconomic aggregates. The forecasts do not incorporate all financial information received in equal measures, implying the presence of information rigidities in the incorporation of credit spread information.     

A UNIFIED PRESENTATION OF COMPETITION ANALYSIS IN TWO-SIDED MARKETS

The goal of this paper is to present quantitative tools to manage competition policy analysis in two-sided platforms, based on a common framework for transaction and non-transaction platforms. We explore tools for relevant market definition [Critical Loss Analysis and a small but significant non-transitory increase in price (SSNIP) test], unilateral effects indicators [Upward Pricing Pressure (UPP) and Gross Upward Pricing Pressure Index (GUPPI)] and tests for exclusionary practices. We review dispersed results in the literature and fill the gaps where appropriate. We highlight the required changes from the usual one-sided market framework and tools. While discussions of antitrust tools can be found in specialized forums devoted to advances in competition policy analysis, we organize the material in an integrated framework.     

Do institutional investors drive corporate transparency regarding business contribution to the sustainable development goals?

Institutional investors show increasing interest in how companies align their corporate social responsibility strategies with the sustainable development goals (SDGs) proposed by the United Nations (UN). The information disclosed in this regard is essential to know and monitor business contribution to the 2030 Agenda. In this paper, we analyze the influence that institutional investors have on the adoption of the disclosure strategy established by UN and the Global Reporting Initiative (GRI)—GRI‐SDG Compass. The results obtained for a sample of 989 international companies, which prepare their sustainability reports following the GRI guidelines, show that ownership by foreign investors, pension funds, and “other” investors boosts the relevance of the information disclosed in relation to the 2030 Agenda. On the contrary, government, financial institutions, and cross holdings have no impact on the information systems developed.     

A functional time series analysis of forward curves derived from commodity futures

We study forward curves formed from commodity futures prices listed on the Standard and Poor’s-Goldman Sachs Commodities Index (S&P GSCI) using recently developed tools in functional time series analysis. Functional tests for stationarity and serial correlation suggest that log-differenced forward curves may be generally considered as stationary and conditionally heteroscedastic sequences of functions. Several functional methods for forecasting forward curves that more accurately reflect the time to expiry of contracts are developed, and we found that these typically outperformed their multivariate counterparts, with the best among them using the method of predictive factors introduced by Kargin and Onatski (2008).     

GRADING JOURNALS IN ECONOMICS: THE ABCS OF THE ABDC

Many institutions and governments grade academic journals for the evaluation of research. In this paper, we implement a multi-bibliometric methodology for the evaluation of such a list of journal grades. We examine the grades assigned by the Australian Business Deans Council (ABDC) for over 750 journals in the fields of economics and statistics. Firstly, we generate up to 48 bibliometric-based grades for each journal based on the grade distribution implied by the ABDC. Secondly, we categorize the bibliometrics employing a cluster analysis of an interrater agreement statistic. Thirdly, we present a visualization of the consistency of the grading by journal. Finally, we list those journals where the majority of the matched bibliometrics indicate a higher or lower grade than their ABDC grade.     

A gramscian perspective on field dynamics. The case of the privatization of Italian steel industry

Institutional fields are not static, they undergo times of fragmentation and times of settlement. Neo-institutional research has long explained the settlement of fields as either the effect of political manoeuvring of actors, or of discursive activity influencing cultural codes, narratives and symbols. But can these processes really be considered in isolation? In this paper, we propose to adopt a comprehensive view on fields’ dynamics, one that embraces the interaction of political and discursive manoeuvring to explain how fragmented fields manage to settle. To do so, we build on the Gramscian concept of hegemonic practices as discursive and political processes that integrate cultural equivalence among actors with political alliances based on aligned interests. Hegemonic practices align actors in a new historical bloc (a new settlement). Through this lens, we interpret the case of the Italian State steel privatization (1984–1995) and propose a process model explaining what yields fields’ dynamics from fragmentation to settlement. The model highlights the action of diffused agency in field dynamics, thus overcoming the obsolete challenger/incumbent view, and the need of becoming a historical bloc for alliances to stabilize a field.     

Is the environment‐friendly factor attractive to customers when purchasing electric vehicles? Evidence from South Korea

In a bid to reduce greenhouse gas emissions, several countries worldwide are implementing policies to promote electric vehicles (EVs). However, contrary to expectations, the diffusion speed of EVs has been rather slow in South Korea. This study analyzes consumer preferences for the technological and environmental attributes of EVs and derives policy and environmental implications to promote market diffusion of EVs in South Korea. We conduct a choice‐based conjoint survey of 1,008 consumers in South Korea and estimate the consumer utility function using a mixed logit model considering consumer heterogeneity. Based on the consumer utility function, we analyze consumers' willingness‐to‐pay (WTP) for EV attributes such as driving range, charging method, charging time, autonomous driving function, carbon dioxide (CO₂) reduction rate, and purchase price. The results indicate that the current low acceptance of EVs is due to their relatively high price and lack of a battery charging technology that satisfies consumers' expectations of the charging method and time. One interesting finding is that Korean consumers have a relatively higher WTP for the CO₂ reduction rate of EVs than consumers in other countries; however, they do not consider CO₂ reduction over other technological attributes when choosing EVs. This implies that the rate of CO₂ reduction of EVs is not an important factor for South Korean consumers when buying EVs. We also calculate the effect of CO₂ reduction with the market penetration of EVs and find that CO₂ reduction through the diffusion of EVs depends on the country's electricity generation mix.     

SYSTEMATIC LITERATURE REVIEW OF TOURISM GROWTH NEXUS: AN OVERVIEW OF THE LITERATURE AND A CONTENT ANALYSIS OF 100 MOST INFLUENTIAL PAPERS

This study performs the first citation-based systematic literature review of the tourism-growth nexus. The citation analysis provides a bird's eye view of this literature, which, in turn, identifies the sources of knowledge in terms of most influential journals, authors, and articles. A detailed content analysis of 100 most influential papers has been generated on the nature of the study, variables used, country of analysis, type of analysis, the methodology, and the direction of causality. In total, 284 papers were found relevant in the Scopus database using a comprehensive list of keywords. The citation analysis reveals that Tourism Management is the leading journal with a total of 2527 citation counts, whereas Tourism Economics is the leading journal with a total of 41 publications on this topic. Juan Gabriel Brida is the most prolific author, whereas Lee and Chang (2008) is recognized as the most influential paper. The content analysis reveals that 58% have applied time series, and 38% have used panel data analysis. Tourism causing growth is the leading result of both time-series and panel studies. International tourism receipts/earnings/expenditure and the number of international tourist arrivals are the most widely used variables to measure tourism.