The complex farm-level relationship between environmental performance and productivity: The case of carbon footprint of Lombardy farms

Baldoni, Edoardo; Coderoni, Silvia; Esposti, Roberto

doi:10.1016/j.envsci.2018.07.010

Cited by 31 publications

(13 citation statements)

References 22 publications

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“…methane or nitrous oxide) can be expressed as CO 2e by multiplying the amount of the GHG by its global warming potential (GWP). 2 For Italian agriculture case study, both micro and macro level have been explored (see among others: Rete Rurale Nazionale 2012; Coderoni and Esposti 2014; Baldoni et al 2017Baldoni et al , 2018. Canavari and Coderoni Agricultural and Food Economics (2020) Carbon footprint labels in the agri-food sector According to Miranda-Ackerman and Azzaro-Pantel (2017), "New consumer awareness is shifting industry towards more sustainable practices, creating a virtuous cycle between producers and consumers enabled by eco-labelling".…”

Section: Introductionmentioning

confidence: 99%

Consumer stated preferences for dairy products with carbon footprint labels in Italy

Canavari

Coderoni

2020

Agric Econ

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Carbon footprint (CF) labels on agri-food products represent one of the most important tools to convey information to consumers about the greenhouse gases emissions associated with their purchase behaviour. Together with the growing interest of consumers in CF labels, the subject has gained attention also in the scientific literature, and formal evaluations of consumer response to carbon labelling have been published. Studies in this area aim at analysing consumers' preferences for buying products with a lower CF label or their willingness to pay (WTP) for these products. The objective of this paper is twofold. First, the study proposes a review of the literature that so far has analysed consumer WTP for CF label, focusing on Italian consumers. Second, it uses the results of two surveys of consumers' attitudes towards dairy products with a lower CF label to analyse the factors determining a positive stated WTP. Results point out that a positive WTP for lower CF products is more likely to be declared by respondents who believe that buying products with less environmental impact can combat climate change. Conversely, highly pricesensitive consumers are less likely to be willing to pay more for CF-labelled products.

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Section: Introductionmentioning

confidence: 99%

Consumer stated preferences for dairy products with carbon footprint labels in Italy

Canavari

Coderoni

2020

Agric Econ

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“…These kinds of methods are not outdated, because they are relatively simple and have advantages in some current studies. For example, some scholars make good use of them to calculate TFP with micro data [16,17].…”

Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Characteristics of Agriculture Green Total Factor Productivity in China, 1998–2016: Based on More Sophisticated Calculations of Carbon Emissions

Huang

et al. 2019

IJERPH

100

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Environmental costs should be taken into account when measuring the achievements of China’s agricultural development, since the long-term extensive development of agriculture has caused huge environmental pollution. This study took agricultural carbon emissions as an undesired output to estimate the agricultural development efficiency in 31 provinces of China from 1998 to 2016, based on the green total factor productivity, as assessed by the slacks-based measure directional distance function and constructing the global Malmquist–Luenberger index. We measured agricultural carbon emissions in terms of five aspects: agricultural materials, rice planting, soil, livestock and poultry farming, and straw burning, and then compared the green total factor productivity index and the total factor productivity index. The study came to the following conclusions: (1) the green technology efficiency change was smaller than the technology efficiency change at first, but the gap between them is narrowing with time, such that the former is now larger than the latter; (2) the green technology efficiency was in a declining state and the green technology progress was increasing, promoting the green total factor productivity growth, from 1998 to 2016; and (3) China’s agricultural green total factor productivity increased by 4.2% annually in the east, 3.4% annually in the central region, and 2.5% annually in the west.

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“…For instance, based on the development of developing countries and EU countries as examples, Mielnik et al [36] and Kortelainen [37] proposed that carbon productivity can be used to test the low-carbon development capacity of an economy. Taking the Italian Agricultural Group as the research object, Baldoni et al [38] empirically studied the influence of productivity and environmental performance in agriculture using GMM-SYS estimation. The research results confirmed the existence of such a relationship.…”

Section: Research On the Relationship Between Carbon Productivity And Low Carbon Economic Growthmentioning

confidence: 99%

Energy Consumption Transformation, Cleaner Production, and Regional Carbon Productivity in China: Evidence Based on a Panel Threshold Model

Ding

Han

2021

IEEE Access

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It has become an urgent issue for all countries to ease the sharp conflict between economic growth and ecological conservation. The fundamental way to achieve low-carbon economic growth is to make the energy consumption structure upgrade and develop towards a cleaner direction. Standing at the point of clean production, this study empirically analyses the nonlinear mechanism of the transformation of energy consumption structure on China's regional carbon productivity by using the threshold model based on the inter-provincial data from 2009 to 2017 (30 provinces in China). The research shows that there are significant differences in cleaner production levels in different parts of China. In contrast, the cleaner production capacity in most regions has been significantly improved during the sample period. It shows the energy consumption structure transformation has a remarkable double threshold effect on regional carbon productivity in China. While clean production keeps crossing the threshold value, the effect direction of energy consumption transformation on regional carbon productivity changes from negative to positive, with both the coefficient value and significance increasing. According to the research results, the paper focuses on adjusting energy resource consumption and improving the clean production level. Eventually, some policy inspirations are proposed for the lower emissions and sustainable process of the Chinese economy.INDEX TERMS Energy consumption transformation, cleaner production, regional carbon productivity, threshold model, heterogeneity, china.

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The complex farm-level relationship between environmental performance and productivity: The case of carbon footprint of Lombardy farms

Cited by 31 publications

References 22 publications

Consumer stated preferences for dairy products with carbon footprint labels in Italy

Consumer stated preferences for dairy products with carbon footprint labels in Italy

Spatial-Temporal Characteristics of Agriculture Green Total Factor Productivity in China, 1998–2016: Based on More Sophisticated Calculations of Carbon Emissions

Energy Consumption Transformation, Cleaner Production, and Regional Carbon Productivity in China: Evidence Based on a Panel Threshold Model

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