Suchergebnisse

Carbon tax is an important carbon emission mitigation tool and has been widely recognized as an efficient mechanism for slowing down global warming. The imposition of a carbon tax will, however, inevitably affect income distribution, as a household's income level influences its priorities regarding consuming the affected goods. This will have important implications for the government, which will have to formulate policies that can achieve efficiency as well as equity. In this study, we apply the input–output price model to estimate the distribution effects of a carbon tax for urban as well as rural areas in China. Our results show that the price increases due to carbon taxes affect rural areas more than urban areas. The Suits index in rural areas is −0.1928, while the value in urban areas is −0.0588. This indicates carbon tax is regressive in all areas, especially the rural ones, and there is a need to formulate suitable policy measures to alleviate a possible widening income gap among income groups and between urban and rural areas.

AbstractDespite the abundance of literature on agricultural price transmissions and unexpectedly disrupted value chains from infectious disease outbreaks such as bovine spongiform encephalopathy and COVID-19, the importance of research on price connectivity in the international beef markets has largely been ignored. To assess agricultural price transmission issues, error correction-type models (ECMs) have been predominantly employed. These models, however, suffer a deficiency in that the method is incapable of depicting time-variant linkages between prices. This article examines the connections between global and local prices, as well as price volatility in the beef sector. Our analysis uses a generalised autoregressive conditional heteroscedasticity (GARCH) model with the dynamic conditional correlation (DCC) specification that enables us to identify market connection intensity dynamics. We pay assiduous attention to structural changes in the overall research processes to enhance the reliability of estimation. For the first time in meat or grain price transmission research, our autoregressive models have been developed with structural break dummy variables for DCC. The principal findings are that (1) local retail prices for Azerbaijan, Georgia, Japan, Kazakhstan, Kyrgyzstan, Tajikistan and the UK showed a structural change in mean or variance, all of which were identified after the global food crisis from 2007–2009, (2) international prices unidirectionally Granger-cause regional prices in Georgia, Tajikistan and the United States in both mean and volatility (accordingly, no country exhibited price or price-volatility transmission from regional to international markets), and (3) volatility liaisons between global and local beef markets are generally weak, but price volatility exhibited closer synchronisation around the 2008 global food crisis, which created structural changes during the period. This finding implies that national governments should shield domestic from global markets by implementing trade restrictions such as quotas or taxes in a global emergency.

Existing literature has not yet identified the common determinants of price volatility transmission in agricultural commodities from international to local markets and has rarely investigated the role of self-sufficiency measures in the context of national food security. We analyzed several factors to determine the degree of volatility transmission in wheat, rice and maize prices between world and domestic markets using GARCH models with dynamic conditional correlation specifications and panel feasible generalized least square models. Our findings indicate that a grain autarky system can reduce volatility passthroughs for three grain commodities. While the substitutive commodity consumption behaviour between maize and wheat buffers the volatility transmissions of both, rice does not function as a transmission-relieving element for the volatility implying that rice is not a substitute for wheat or maize consumption; grain consumption proves a more effective substitute than cereal self-sufficiency for insulating passthroughs from global markets. These findings may help the governments of developing nations to protect their domestic food markets from the uncertain movements of foreign markets and may thus improve food security.

AbstractThis study explores the relationships among the variables: willingness to quarantine, perception of the epidemic, willingness to do outdoor activities, government credibility, and public morality. To understand these relationships, it integrates theories including epidemic prevention and control, government credibility, public morality, and social network systems. Structural equation modeling (SEM) with bootstrapping estimation was conducted using data calculated from 368 healthy citizens who are quarantining at home due to COVID‐19 in Chinese cities that have launched a first‐level primary public safety incident response. The results show that residents' perception of the epidemic has a positive effect on their willingness to quarantine, and willingness to do outdoor activities has a negative effect. Moreover, government credibility and public morality have a mediating effect on the relationship between the perception of epidemic and willingness to quarantine. What is more, government credibility has a moderating effect on the relationship between willingness to do outdoor activities and willingness to quarantine. We discuss the implications of these results for beating future epidemics that may break out.