Isabelle Thomas (p), Sonia Trabelsi

The relationship between urban living environment and health has been widely tackled in the past years (Twohig-Bennett et al., 2018). Generally, exposure and proximity to natural environments are considered to have beneficial effects on human health (Hartig et al. 1991; de Vries et al. 2003). Unfortunately, data about health are usually scarce and typically protected for privacy issues. But recent advances in data collection has led to the storage of massive amount of data on individuals, among which medication purchases. In our case study, we try to observe links between health status, surrogated by medication reimbursement data, and socio-economic and environmental factors. If some geographical analyses about such data have consequently appeared in recent scientific literature (see e.g. Wangia and Shireman, 2013), results are often not comparable and studies looking at spatial variation in medication consumption within a country are rare (Cheng et al., 2011).

In Belgium, a central agency (IMA-AIM) systematically collects and stores data on medication reimbursement across the entire country, at different administrative levels. We here isolate six medication types associated to a priori defined pathologies representing environment-associated health troubles (asthma, allergies, autoimmune diseases, depression and anxiety, dyslipidemia, and cardiovascular issues). After a first step of data cleaning and standardizing by age, the paper first presents and critically comments the choropleth maps of the different proxies. Then, we test the correlations between the selected health proxies with some standard socio-economic and environmental variables, by means of Pearson correlations, clustering and principal component analyses. Surprisingly enough, environmental and socioeconomic components are totally independent of the proxies used while all health proxies are positively correlated together whatever the sickness considered.

Our results show that medication reimbursement is not an environmentally-driven problem, but rather suggest a public health issue (health policy, education of the medical doctor, pharmaceutical commercial activities, …). This study warns us on the use of medication data as a proxy for health issues, and to be careful in the interpretation of the results.

Juin-Jen Chang, Yi-Ling Cheng (p), Shin-Kun Peng

This paper provides implications of firm heterogeneity for global pollution and trade liberalization in a model of endogenous markups and non-compliance with environmental regulations. We show that firms with heterogeneous productivities respond differently to a uniform environmental regulation, which changes the market competition structure within a country and across countries, and disentangles the interaction effects of environmental regulations and trade liberalization. In autarky, efficient firms are favored by environmental regulations but they may produce more emissions via the non-compliance to escape the regulation and maintain their competitiveness. In a symmetric two-country open economy, trade liberalization can break the output-environment trade-off, not only increasing the world-wide output but also decreasing global pollution emissions. Under asymmetric environmental regulations, a unilateral increase in the emission tax decreases the average productivity in this country if openness to trade is substantially high, which contrasts with the effect under autarky whereby the average productivity increases with the emission tax. Our welfare analysis shows that there exists a U-shaped relationship between the optimal emission tax and openness to trade regardless of whether under tax harmonization or tax competition. Trade liberalization unambiguously decreases global pollution emissions under tax harmonization but it may increase global pollution emissions under tax competition.

Dmitry Kovalevsky (p), María Máñez Costa

Weather index-based insurance is a promising insurance scheme that might be particularly relevant for the agricultural sector in many developing countries. In particular, it might be efficient in regions prone to agricultural droughts. Weather index-based insurance policies might be more affordable to farmers, as the payouts in these insurance schemes are based on weather indices objectively determined for the specific agricultural regions, and therefore the costly individual loss assessment is not necessary. We develop a stochastic model to simulate the demand for insurance policies in a drought-prone region. For the proposed modelling approach, it is essential that weather and climate services provide forecasts of the weather index on which the insurance scheme is based, as tailored products for regions vulnerable to droughts. In such a case, among other factors, the demand for the insurance policy might depend on the skill of available seasonal weather forecast, from which the weather index forecast is derived. We compare different strategies of individual farmers regarding weather index-based insurance products. One of the findings of this modelling study is that decisions based on a forecast for the coming season with very low skill might provide less economically successful strategies for the farmers than the decisions made when the forecast is ignored or is unavailable. Therefore, presented modelling results suggest that both strategies of individual farmers and the dynamics of aggregate demand for insurance policies might be sensitive to the skill of available regional forecast.

Sandy Dall'erba (p), Andre Avelino

Recent studies on the impact of climate change anticipate a significant decrease in both the availability and quality of water resources in the next half-century, which will directly impact domestic and international food supply chain linkages. In the U.S., agricultural production requires less irrigated water than in the past but it is still responsible for more than a third of total water withdrawals. To better understand the evolution of water use in this sector, we perform a structural decomposition analysis over the 1995-2010 period using the Exiobase 3 database. More precisely, we emphasize i) the evolution of water withdrawals for 8 different crops and 6 livestock categories, ii) the difference in results from using the observed water consumption data from the U.S. Geological Survey vs. Hoekstra’s water footprint data, and iii) the trends in the pre-crisis period (1995-2005) and after it (2005-2010). Our results show that the pre-crisis period experienced an overall decline in water withdrawals but oil seed crops (which include soybeans) increased their water use primarily because of greater water intensity and changes in international interindustrial trade patterns. This increase persisted in the post-2005 period but was driven primarily by direct exports to industries and changes in the average global expenditure structure. We also find that the evolution in the production structure of the U.S. food manufacturing sector contributed to an increase in water use in agriculture pre-2005 but to a decrease post-2005. Livestock has also shown a decline in water use during the entire period, mainly driven by the dynamics in water use for cattle (beef and milk cows). Overall, these results will help develop future water-saving strategies in the U.S. as the country, like its trade partners, will meet increasing challenges to secure food availability in the face of climate change.