to facilitate the evaluation of the Danida-supported Agricultural and Rural Development Sector Program Support (ARD-SPS). In subsequent rounds, a part of the sample was replaced in each round to correct for aging of the original sample. In total, approximately 3,000 households were sampled in each round from 2008 onwards. We restricted our sample to households covered in all four rounds between 2008 to 2014, the latest round of VARHS to which we were able to gain access. Matching this with the administrative data left us with 509 households in each round of the VARHS spread across 73 communes in the RTP3 sample; a total of 2,036 observations in four consecutive rounds, spanning an eight-year period.

# _Administrative data_

We used administrative data on road improvements at the level of each road. This data included: type of activities carried out under RTP3 (classified into rehabilitation, periodic maintenance, and routine maintenance), the dates when these activities were carried out, and the location of the road. We retrieved these data from project management units located within the DoTs in each province with significant assistance from the central project management unit located in the Department of Roads Vietnam (DRVN) in Hanoi.

The decentralized implementation structure both impeded easy access to administrative data and lowered the quality of data we were eventually able to retrieve. Although some project data were maintained centrally, including by the World Bank, they were not at the level of detail sufficient to carry out an impact evaluation. Data on locations of each road, activities, and timelines were only maintained in the provincial DoTs responsible for the implementation of the project. Collecting the data took several months and was an iterative process based on conversations with staff of the DRVN and provincial DoTs. We learnt in the process that data on non-RTP3 activities and GIS data on roads were prohibitively difficult to retrieve, if not nonexistent. The data on the pre-intervention quality of the road were not available either. In the end, we were able to collect data covering project activity, start and end dates, and details of the road segment improved from 17 of the 33 project provinces.

The resulting data set covered 1,369 road segments, which pass through 1,222 communes in 240 districts. Activities are classified into four types of improvements—road rehabilitation, periodic maintenance, routine maintenance, and repairs due to flood (Table A.2). Repairs due to flood are an emergency response. Including them in estimation of RTP3 impacts could conflate the impact of the flooding with the impact of response to the disaster. Consequently, we dropped RTP3 roads where these emergency repairs due to floods took place. This left us with 1,350 roads.

# _Qualitative data collection_

We complemented these quantitative data with qualitative data collected from three RTP3 project sites. The objective of qualitative data collection was to understand the mechanisms through which better roads affected socio-economic outcomes. We placed specific emphasis on capturing gender-specific factors, which may facilitate or hinder benefitting from improved rural roads.

Our primary data collection took place between October 21 and November 2, 2018. We selected one RTP3 road in three provinces that were covered in VARHS: Lào Cai, Nghệ An, and Quảng Nam. We designed the 8