correlative. Suich et al. (2015) review the evidence of research into the relationship between ecosystem services and poverty alleviation and conclude that “a considerable gap remains in understanding the links between ecosystem services and poverty, how change occurs, and how pathways out of poverty may be achieved based on the sustainable utilisation of ecosystem services.” The main contribution of this paper is to provide causal estimates of the impact of environmental quality on poverty reduction. In addition, insights into the importance of environment relative to other factors such as infrastructure development or urbanization will be discussed. In particular, several contributions to existing literature are offered: (a) We use a global subnational data set, (b) we use monetary poverty rates that emerge from survey and census estimations rather than highly modeled measures that may induce multicollinearity with the explanatory variables, (c) we use not one, but three different measures of environmental quality, one for soil fertility and two for vegetation vigor, and (d) we do not draw evidence from cross‐sectional evidence only (which likely suffers from omitted variable bias), but also exploit variance over time by implementing a panel fixed effects model. With these methodological refinements, we obtain results that underline the importance of soil and vegetation quality in poverty reduction.

# **2. Empirical Strategy**

# **a. Data**

We create a unique geospatial data set linking environment and natural resource measures to poverty and other human development indicators at the subnational level. The geographical unit of analysis of the data set is the administrative unit 1 level, commonly referred to as “province” level, because this is the finest‐grained level at which the poverty data set is available.<sup>3</sup> This rich data set allows us to specify a range of different models to examine the relationship of environmental quality (and degradation) and poverty.

# **Poverty and GDP per capita (outcome measures)**

The measurement of poverty we use is the headcount ratio of people falling below $1.90 per day. Even though this is a narrow definition of poverty,<sup>4</sup> it is the official international poverty line and allows us to draw from country poverty maps that the World Bank has helped produce over the last 30 years. We “stitch together” a global map of sub‐national poverty measures and pool several years of observations for several countries, creating an unbalanced poverty panel (see table 6 for the detailed descriptive statistics on the poverty observation frequency by country). For the panel specifications, we use the countries in table 6 that have repeated poverty observations. For the cross‐sectional specification, we use the latest available observation per country.

> 3 Certain poverty maps were available at the administrative unit 2 level, commonly referred to as the “district” level. However, time‐series data– necessary for furnishing a panel data set – were only available at the province level. 4 There are other very useful measures of poverty such as the Multidimensional Poverty Indicator (MPI), which is also available regionally (see <u>Alkire et al, 2015).</u>

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