_Environmental income_ is in the PEN guidelines defined as “incomes (cash or in kind) obtained from the harvesting of resources provided through natural processes not requiring intensive management”. It includes income from natural forests ( _forest environmental income_ ) and non-forest wildlands such as grass-, bush- and wetlands, fallows, but also wild plants and animals harvested from croplands ( _non-forest environmental income_ ). Thus all forest income, except income from plantations, is defined as environmental income.

All incomes are transformed to US dollar (USD) purchasing power parity (PPP) rates of the survey year (2005-2009).<sup>9</sup> For inter-household comparisons of incomes and asset holdings we use adult equivalent units (AEU). A range of methods is available for calculating adult equivalents (Deaton 1997). We use the OECD adult equivalence scale: the first adult counts as 1 unit, the following adults (>15 years) ones count as 0.7, while children count as 0.5. For the regressions underlying the income predictions we separate between different household member groups. We differentiate between males and females, and children (<15), adults (15-65) and elders (>65).

The PEN survey also asked households if they had experienced any “major income shortfalls or unexpectedly large expenditures during the past 12 months”, i.e., the period covered by the income survey. We categorized them _ex post_ into the following categories: (i) _income shock_ : serious crop failure, lost wage employment or delays in payments of products during the period covered by the income surveys; (ii) _labor shock_ : serious illness or death of a productive age household member; and (iii) _asset shock_ : loss of land, livestock or other major losses of assets. Households were also asked about the severity of the chock, distinguishing between moderate and severe ones.

# **3.2 Climate and forest cover data**

To relate the household data to climatic conditions we use the gridded climate data of the Climate Research Unit of the University of East Anglia (CRU TS3.21). The CRU data contain monthly time series of temperature, precipitation and other climate variables spanning the period from 1901 to 2012 and covering the whole globe with 0.5x0.5 degree resolution. It is based on the analysis of over 4,000 individual weather station records (Harris et al. 2014).

A normal climate is defined as the mean precipitation (mm per year) and temperature (degrees Celsius) in the village during the period 1981-2010. Weather anomalies refer to deviations in precipitation and temperature during the survey period, defined as the year that starts two month before the first interview in the respective village. We use the term “weather anomaly” rather than “climate shock”, as it refers to only one year. For further details about the CRU data, we refer to Noack et al. (2015).

In much of the analysis we distinguish between wet and dry villages (areas), using 1,500 mm of rain during the 1981-2010 period as a cut-off point. The impacts of more rain, for example, might be very different in the two areas. All PEN sites in Latin America are in wet areas, while most of the African sites are in dry areas. The exceptions in Africa are the wet sites in Cameroon and Nigeria. India and Nepal in South Asia have a mix of wet and dry sites, while China has the only dry site in East Asia.

Finally, we use data from Hansen et al. (2010) to provide estimate of tree canopy cover and change in tree canopy cover for the period 2000-2010. The data use annual MODIS-satellite based estimations of tree canopy cover at 250 m spatial resolution globally. The data used in this paper are

> 9 We used the PENN World Tables, ver. 7.0 <u>http://pwt.econ.upenn.edu/php_site/pwt_index.php.</u>

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