The COVID-19 pandemic is a global crisis affecting everyone. Yet, its challenges and countermeasures vary significantly over time and space. Individual experiences of the pandemic are highly heterogeneous and its impacts span and interlink multiple dimensions, such as health, economic, social and political impacts. Therefore, there is a need to disaggregate "the pandemic": analysing experiences, behaviours and impacts at the micro level and from multiple disciplinary perspectives. Such analyses require multi-topic pan-national survey data that are collected continuously and can be matched with other datasets, such as disease statistics or information on countermeasures. To this end, we introduce a new dataset that matches these desirable properties -the Life with Corona (LwC) survey -and perform illustrative analyses to show the importance of such micro data to understand how the pandemic and its countermeasures shape lives and societies over time.

Farmers' aversion to risk can play a key role in how they make production decisions on the farm. While there is evidence that experience of shocks could alter risk preferences, most of this research relies on just one dimension of risk aversion. Using a series of incentivized lottery games, we estimated a broader set of risk preference coefficients that correspond to cumulative prospect theory, namely the probability weighting function, the curvature of the value function and loss aversion, along with a coefficient for ambiguity aversion. We attempted to understand how past harvest shocks and the sociodemographic characteristics of maize farmers in southern Mexico related to these preference parameters. Our results provide evidence that experience of more severe harvest losses is associated with greater risk aversion and stronger overweighting of small probabilities. Greater harvest shock severity was not related to loss or ambiguity aversion.

It has been shown consistently in the literature that early life exposure to extreme weather events affects children's nutritional status and related long-term health and well-being outcomes. The effects of weather shocks other than rainfall, as well as heterogeneous effects among population subgroups and moderators of this relationship, however, are less well understood. By combining a rich three-wave representative household panel dataset from Kyrgyzstan, a country where weather extremes such as droughts, floods but also cold spells are predicted to increase in frequency and severity due to climate change in the near future, with location-matched weather data, this paper analyzes how different weather shocks (cold winter, drought, excessive rainfall) affect the probability of stunting of children under five. Using fixed effects regression models, we find that children under 20 months are most severely affected by all three types of early life weather shocks. Most notably, we find that cold shocks experienced in winter increase the probability of stunting, and that this effect is particularly pronounced for households that mainly rely on electricity for indoor heating, potentially due to frequent power cuts occurring in winter. We do not find rural/urban differences, but we find some seasonal effects of shock exposure. Overall, effects are driven by boys, even though we do not find statistically significant gender differences. Identifying the geographical and sociodemographic subgroups of children most vulnerable to extreme weather events can support the design of targeted policies addressing child malnutrition. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

When faced with uncertain events, decision-makers form expectations about the events' likelihood of occurrence. However, the drivers and moderators of such expectations are still poorly understood, especially for farm decision-makers in developing countries whose incomes are very risky by nature. This article analyses the dynamic shock expectation formation process of farmers in Kenya with regard to a range of shock events using a unique panel dataset. The results suggest that farmers are more likely to update their expectation regarding a specific adverse shock when they have recently been affected by that shock or by more shocks in general. In case of price shocks, farmers are also more likely to update expectations when a larger proportion of fellow village members was affected. However, household wealth moderates the relationship between shock expectation and experience, such that wealthier households are less likely to update their expectations following a shock. A better understanding of the drivers of expectation formation can help in the design of better risk management instruments that increase farmers' resilience.

Gender differences (GD) in mental health have come under renewed scrutiny during the COVID-19 pandemic. While rapidly emerging evidence indicates a deterioration of mental health in general, it remains unknown whether the pandemic will have an impact on GD in mental health. To this end, we investigate the association of the pandemic and its countermeasures affecting everyday life, labor, and households with changes in GD in aggression, anxiety, depression, and the somatic symptom burden. We analyze cross-sectional data from 10,979 individuals who live in Germany and who responded to the online survey “Life with Corona” between October 1, 2020 and February 28, 2021. We estimate interaction effects from generalized linear models. The analyses reveal no pre-existing GD in aggression but exposure to COVID-19 and COVID-19 countermeasures is associated with sharper increases in aggression in men than in women. GD in anxiety decreased among participants with children in the household (with men becoming more anxious). We also observe pre-existing and increasing GD with regards to the severity of depression, with women presenting a larger increase in symptoms during the hard lockdown or with increasing stringency. In contrast to anxiety, GD in depression increased among participants who lived without children (women > men), but decreased for individuals who lived with children; here, men converged to the levels of depression presented by women. Finally, GD in somatic symptoms decreased during the hard lockdown (but not with higher stringency), with men showing a sharper increase in symptoms, especially when they lived with children or alone. Taken together, the findings indicate an increase in GD in mental health as the pandemic unfolded in Germany, with rising female vulnerability to depression and increasing male aggression. The combination of these two trends further suggests a worrying mental health situation for singles and families. Our results have important policy implications for the German health system and public health policy. This public health challenge requires addressing the rising burden of pandemic-related mental health challenges and the distribution of this burden between women and men, within families and for individuals who live alone.

The Covid-19 pandemic and its economic fallout continues to disrupt global food systems with detrimental impacts on food security and nutrition, particularly in lowand middle-income countries (LMICs) (UN, 2020). It is estimated that the number of people in acute food insecurity will almost double between 2019 and 2020 (WFP, 2020a), and malnutrition and child wasting is predicted to increase drastically (Headey & Ruel, 2020). Border restrictions and lockdowns put planting, harvests and processing at risk, constrain transport to markets, destroy incomes and, in particular, disrupt food services and retail (Swinnen & Mcdermott, 2020). Perishable foods in particular become less accessible, especially for urban and low-income consumers. Price increases combined with falls in income are likely to change dietary patterns in favour of cheaper, less nutritious and highly processed foods, raising the risk of a double burden of malnutrition (Pries et al., 2019). In many areas of the world, Covid-19 is exacerbating existing food crises. This policy brief recommends effective interventions to increase food and nutrition security in LMICs as a response to Covid-19 based on rigorous evidence, and highlights impact pathways and specific adaptations in the context of the pandemic. KEY MESSAGES

For farmers in developing countries, the combination of both risk aversion and the lack of insurance is often a major impediment to adoption of productivity-enhancing technologies, such as higher yielding hybrid seed. In a framed field experiment with Mexican maize farmers, we investigate whether bundling hybrid seed with an insurance scheme can increase its adoption, while also controlling for risk aversion. We test insurance schemes with different levels of risk coverage and premium subsidies and find that (1) all schemes significantly increase the degree of adoption of the higher yielding seed, (2) partial insurance schemes perform worse than full insurance, (3) weather index insurance with geographical basis risk performs no worse than indemnity insurance, and (4) premium subsidies significantly increase the adoption effect of indemnity insurance, but not that of index insurance.

In the absence of formal financial markets, many poor households rely on risk sharing networks to protect themselves against adverse events. In this paper we present a model that explains the impact of formal insurance on informal risk sharing and, subsequently, the dynamics of other-regarding preferences. We use a field experiment to test the predictions of the model with rural households in Mexico. Consistent with the model predictions, we find that when shocks are collective, there is a crowding-out effect on transfers and a decrease in trust on insured participants. However, when shocks are idiosyncratic, we fail to confirm the predictions of the model. Transfers to non-insured members are significantly higher when insurance is available to some of the network members than in a control treatment when insurance is not available. This unexpected crowding-in effect on transfers leads to an increase in trust among non-insured participants. These findings suggest that there is a need to find optimal insurance designs that minimizes the crowding-out effect of formal insurance on informal risk sharing and other-regarding preferences.

The first paper of this dissertation in Chapter II, “Insurance for Technology Adoption: An Experimental Evaluation of Schemes and Subsidies with Maize Farmers in Mexico”, analyzes experimentally how bundling the purchase of a risky technology, namely a higher yielding maize seed variety, with different insurance schemes, affects the total take-up of that variety. In this regard, the paper looks at the effects of (1) partial insurance versus full insurance, (2) geographical versus local basis risk, and (3) fair versus below-fair premium. This is the first paper to evaluate insurance schemes with different levels of risk reduction, basis risk and premium subsidies regarding their effect on technology adoption. The results add to the debate on insurance serving as a potential tool for incentivizing agricultural producers to adopt more productive, but more risky technologies, and thereby enabling them to escape poverty (Carter et al. 2016; Fan et al. 2013; Lybbert and Carter 2014; Nicola 2015; World Bank 2013). The second paper in Chapter III, “The Relationship between Farmers’ Shock Experiences and their Uncertainty Preferences - Experimental Evidence from Mexico” addresses the relationship between farmers’ uncertainty preferences, sociodemographic characteristics and their experience of adverse harvest shocks. Uncertainty preferences refer to a range of preference parameters as derived from Cumulative Prospect Theory (Kahneman and Tversky 1979; Tversky and Kahneman 1992), namely risk aversion, loss aversion and probability weighting, as well as ambiguity aversion (Ellsberg 1961). A series of incentivized lottery games are used to estimate these parameters with the sample of Mexican maize farmers, controlling for (1) sociodemographic characteristics and (2) the severity of experienced maize harvest losses. While there are several field studies examining the effect of shocks on risk preferences with subjects from developing countries, only few look at preferences beyond Expected Utility Theory and take into account Cumulative Prospect Theory, and none has looked at ambiguity aversion. Therefore, this paper sheds light on the role that the experience of adverse random shocks, as well as a range of sociodemographic variables, have in explaining one’s uncertainty preferences. The third paper in Chapter IV, “Formal Insurance, Risk Sharing, and the Dynamics of Other-Regarding Preferences”, analyzes how selectively providing formal insurance to members of a risk sharing network affects informal transfers and, subsequently, the dynamics of other-regarding preferences within that network. Many poor households in developing countries are excluded from formal financial markets and therefore rely on the mutual exchange within informal risk sharing networks to protect themselves against adverse income shocks. Social interactions in the aftermath of such shocks have been found to strengthen the social ties among members of these networks, while formal insurance has been found to crowd-out these transfers. Similarly, this third paper finds that when some members of risk sharing networks become formally insured, it affects the informal exchange of transfers among members, as well as their other-regarding preferences. This is the first study to explore the effect of insurance on other-regarding preferences in that context. In order to do so, an incentivized, three-stage experimental design with a baseline and an ex-post measurement of altruism, trust and trustworthiness through dictator and trust games is implemented with random and anonymous groups of three. Between the baseline and the ex-post measurement, a solidarity game is played with the same anonymous groups as in the ex-post measurement of other-regarding preferences, during which the shock structure and the availability of formal insurance are varied exogenously. The findings suggest that the effect of insurance depends on (1) the covariance structure of shocks and (2) is different for the insured and non-insured members within a network. Insurance either decreases trust levels of the uninsured or increases trust levels of the insured subjects towards the other network members, depending on whether the shocks affects one or more than one network member at a time. Trustworthiness and altruism remain unaffected by insurance. Furthermore, the analysis indicates that the results are driven by a change in the dynamics of the transfer behavior within the network induced by formal insurance. Specifically, there is evidence that subjects increase trust levels towards their network members after receiving higher transfers relative to the maximum possible value from them, but not after receiving higher transfers in absolute terms.