Concluding remarks

Wheat is a major commodity that plays a crucial role for food security. The recently observed increase in relative wheat yield variability for Germany – an important wheat producer in the EU – begs the question: Can these increases be traced back to weather changes? Or is it “simply” the result of farms’

adaptations to changing institutional and macroeconomic conditions leading to adjustments in their input-mix? To answer these questions, we analyze relative wheat yield variability consistent with pro-duction economics and agronomic climate impact research. We use a rich set of regional accountancy data and weather variables at the respective phenological stages from 1996 to 2009. Obtained wheat yield volatilities are decomposed into weather- and input- driven categories.

In line with production economics and agronomic research, we find that both inputs and weather im-pact relative yield changes. Common shocks at the national level play a significant role from 2000 onwards, a period characterized by fundamental changes in the EU’s CAP and price booms for agri-cultural commodities. Decomposing wheat yield volatility reveals regionally heterogeneous weather-induced instabilities. Splitting the sample into two sub-periods, we find increases in actual volatility over time, where macro-level shocks including weather extremes contribute. These increases, howev-er, can only in some regions be traced back to joint increases of the weather-induced component and the part caused by adjustments in the input-mix. A number of regions even show decreases in weather-caused volatility over time.

This study is relevant for several reasons. First, future climate impact analyses, which inform policy makers, could utilize this case study as a proof of concept. We could show that omitting inputs would rarely alter our results in a qualitative manner, though would do so quantitatively. Weather impacts and common shocks would be overestimated in the case of leaving out input choices, and adjustments in the input mix would not be discussed at all. We thus contribute to the debate of whether inputs should be a part of climate impact research, where purely statistical approaches are still prominent (Liu et al., 2016; Miao et al., 2016). To conclude, independent of the model type, relating yield and weather offers reasonable results and valid approximations.

Second, these insights support approaches such as the European Commission’s MARS¹¹ project, which is relevant for policy makers for crisis intervention. Considering yield vulnerability by pheno-logical stage at the regional level could improve the seasonal forecasting of potential crop shortages attributable to weather. Better knowledge about yield vulnerability might also help farmers adjust their agronomic management to better cope with downside risk (Chipanshi et al., 2015).

Third, wheat yield vulnerability by phenological stage at the regional level might also be of interest for insurance design and modeling weather risk (Conradt et al., 2015; Odening and Shen, 2014). Since our approach decomposes the influences of weather- and input-related impacts on wheat yields and aver-ages out idiosyncratic shocks, it might help insurers to improve the determination of insurance claims.

For insurers, it might be relevant to only indemnify weather-related yield losses. In addition, a more cost-effective assessment of common weather- related yield losses might enable insurance companies to better cope with systemic risk. This would benefit both the insurer and the insured (cf. Finger, 2013). Insurance-based solutions have recently gained attention because of their potential to contribute to stabilizing farm incomes and thus food security, particularly in regions where smallholder farming prevails (Surminski et al., 2016).

Since many of the European CAP reforms aim to reduce the impact that disbursed subsidies have on input-intensity and to protect the environment at the same time (Levers et al., 2016), our results may further offer insights into how wheat yield variability is related to the interplay between weather, in-put-use and agricultural policy. These may help investigate how to reduce distorting policy impacts on input-intensity, while taking into account that these choices also relate to farmers’ risk mitigation strategies. This in turn is a pre-condition for ensuring secure, resilient and sustainable food produc-tion. The recently-established risk management toolkit under pillar two measures of the EUs CAP might offer a reasonable starting point, though it has seen heterogeneous acceptance among member states thus far. Additionally, as shown by Gaupp et al. (2016), wheat yields are independent at the global level. This is a pre-condition to stabilize food supply by international trade, which could be another option for policy makers (e.g., Brown et al., 2017).

The work presented here displays some shortcomings. First, our data do not allow us to account for land use changes. For instance, farmers might reallocate land for highly subsidized renewable energy plants closer to the farm to save transportation costs. As a consequence, wheat might be reallocated to more distant plots, possibly with lower soil quality. The land used for wheat would not change overall, but yields would be more sensitive to weather impacts. Additionally, yield variability might be subject to technological progress (Chen et al., 2004), which could not explicitly be modelled with our data set. Using improved technology to increase agricultural productivity could be one way to

11

Concluding remarks

36

globally ensure the stable supply of sufficient food quantities (Pardey et al., 2016). As shown by Emerick et al. (2016), against the backdrop of increasing weather risk, particularly new seed varieties with a reduced downside risk have the potential to crowd-in inputs such as fertilizer to increase yields (in addition to the positive agronomic effect on yield). Given that farmland expansion is already at its limit and in some regions only possible at the costs of biodiversity (e.g., Foley et al., 2011), such technical change could contribute to closing yield gaps with less negative environmental impact that the pure intensification of crop production by increasing fertilizers or irrigation would likely have.

Finally, from a producer’s perspective, economic risk matters as well. Output price variation has in-creased in the recent decade and proven to reduce production intensity (Haile et al., 2016). Future research analyzing weather impacts on agricultural production should thus consider farm-level input adaptations to changes in weather- and price-risk as well as policy changes and macroeconomic de-velopments.