Farmland values have traditionally been valued using seasonal temperature and precipitation. A new strand of the literature uses degree days over the growing season to predict farmland value. We find that degree days and daily temperature are interchangeable over the growing season. However, the...

Farmland values have traditionally been valued using seasonal temperature and precipitation. A new strand of the literature uses degree days over the growing season to predict farmland value. We find that degree days and daily temperature are interchangeable over the growing season. However, the...

This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Climate, soil, geography and regional socio-economic variables are matched with farm level data from 37,612 farms across Western Europe. We demonstrate that a median quantile...

This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Data on climate, soil, geography and regional socio-economic characteristics were matched for 37 612 individual farms across the EU-15. Farmland values across Europe are sensitive...

Many nonmarket valuation models, such as the Ricardian model, have been estimated using cross sectional methods with a single year of data. Although multiple years of data should increase the robustness of such methods, repeated cross sections suggest the results are not stable. We argue that...

This research investigates the potential impact of warming on Italian agriculture. Using a detailed dataset of 16,000 farms across Italy, the study examines likely warming impacts in different regions and for different sectors of Italian agriculture. The study finds that farm net revenues are...

Estimated Ricardian models have been criticized because they rely on mean temperatures and do not explicitly include extreme temperatures. This paper uses a cross sectional approach to compare a standard quadratic Ricardian model of mean temperature with a fully flexible daily temperature bin...

WITCH - World Induced Technical Change Hybrid - is a regionally disaggregated hard-link hybrid global model with a neoclassical optimal growth structure (top-down) and a detailed energy input component (bottom-up). The model endogenously accounts for technological change, both through learning...

The stabilisation of GHG atmospheric concentrations at levels expected to prevent dangerous climate change has become an important, global, long-term objective. It is therefore crucial to identify a cost-effective way to achieve this objective. In this paper we use WITCH, a hybrid...

It is widely recognized that technological change has the potential to reduce GHG emissions without compromising economic growth; hence, any better understanding of the process of technological innovation is likely to increase our knowledge of mitigation possibilities and costs. This paper...