structure of these surveys, which includes half of the 9,400 households interviewed in at least two of the three rounds, we assess how environmental risks are related to consumption differences between households and consumption changes over time.

A number of recently‐developed data sets are used to assess 8 environmental risks: (i) outdoor air pollution as a proxy for health risks through respiratory diseases (from Brauer et al., 2015); (ii) tree cover loss as a proxy for the loss of forest resources and ecosystem function (from Hansen et al., 2013); (iii) land degradation as a proxy for productivity decline and agricultural production risks (from Vu et al., 2014b); (iv) slope as a proxy for fragile environments vulnerable to erosion and landslides (from World Soil Database); (v‐vi) long‐term rainfall and temperature variability as a proxy for the variation of weather conditions (from the Climate Research Unit (CRU)); (vii) flood hazards as a proxy for the risks of being flooded (from Bangalore et al., 2016); and (viii) drought hazards as a proxy risks to become affected by drought events (from Winsemius et al., 2015).

Based on these data, the paper addresses three questions: (1) Are there spatial hotspots of high environmental risks and high poverty incidence? (2) Do poorer households live in communes with higher environmental risks? (3) Do environmental risks relate to consumption differences between households and consumption changes over time? These analyses are complementary to other recent work for Vietnam analyzing the income effects of current weather shocks (Narloch, 2016) and the exposure of poor people to future flood risks under different climate change scenarios (Bangalore et al., 2016).

The remainder of this paper is structured as follows. Section 2 describes the data used in the analyses. Section 3 shows the district‐level overlay of environmental risks and poverty in 2010. Section 4 compares environmental risks at the commune level across household groups and urban and rural areas. Section 5 deepens these analyses by presenting results from various regression models explaining consumption differences between households and changes over time by environmental risks at the commune level. Section 6 concludes.

# **2. Data**

This study combines household data from the Living Standard Measurement Surveys, VHLSS 2010, 2012, and 2014, and recent geo‐spatial data measuring environmental risks at the district and commune levels.

## **2.1 Socioeconomic data**

The study mainly relies on household data from the VHLSS 2010, 2012, and 2014. These surveys are conducted by the General Statistics Office (GSO) with technical support from the World Bank in Vietnam. They are nationally and regionally representative and contain detailed information on individuals, households and communes. In total 9,400 households nationwide are included in each round. Half of these households were also interviewed in the previous round so that the data set includes a short‐term panel.

The VHLSS provide detailed information to estimate consumption expenditure, which can be used to estimate poverty rates. This study uses district‐level poverty maps based on estimates from the VHLSS 2010 combined 3