more PSUs with smaller sizes; however, cartography or boundary information is often unavailable for this type of sampling frame like in Armenia and the PSU sizes are still quite large, indicating a costly procedure for household listing as well.<sup>4</sup> Hence, alternative cost-effective national sampling frames based on reasonablysized PSUs with digital boundaries are worthwhile and necessary to facilitate conducting household surveys essential for policy making and research analysis.

The national sampling frame is commonly based on three sources: Census enumeration areas (EAs),<sup>5</sup> subnational administrative boundaries, and a gridded population sampling frame. The census is conducted every 5-10 years or more, depending on financial and administration costs and the nature of the census questions. For example, Armenia’s sampling frame based on census settlements relies on the 2011 Census, which is severely outdated due to demographic changes associated with population displacements and mobility across regions in response to territorial conflicts.<sup>6</sup> The Committee of the Republic of Armenia (ArmStat) conducted a Population Census using a combined approach of administrative data and sampled census in 2022, providing a potential up-to-date national sampling frame. Due to the COVID-19 pandemic, the census was held in a hybrid format, which was the case in many countries. However, this frame, based on a sample of 25% of the addresses in the State Population Register (SPR), is restrictive and unreachable. Because this dataset is inaccessible, it is crucial to have an alternative methodology to update the dataset from the previous census.<sup>7</sup> One of the early techniques to overcome this challenge is grid sampling, where cells—rectangular areas with population estimates—serve as PSUs. The sample frame relies on millions of grid cells publicly available from different data sources, such as the Gridded Population of the World (GPW), which can be accessed through platforms like Google Earth Engine. The grid size varies across data sources, and the choice of the grid size and data provider differs across countries. The grid sampling, however, is subject to some issues. First, grid boundaries are unnatural and can go through buildings and disregard visible features. Second, although the spatial size of the grids is equal, the population size of the grids is unequal. Sparsely populated grids need to be collapsed, and densely populated grids need to be segmented (Qader et al., 2020, 2021).<sup>8</sup> This paper thus provides Armenia’s first digital national sampling frame, successfully developed using various innovative geospatial techniques and datasets. Multiple datasets and maps have also been produced to facilitate the ground survey data collection. The proposed national sampling frame, where PSUs or EAs are automatically created, offers several advantages over other sampling frames (Qader et al., 2021). First, the EAs have natural boundaries like streets and natural elements like rivers. Second, administrative boundaries are strictly respected because the EAs are nested within administrative boundaries by design. While some not widely accepted as a standard approach. This paper does not discuss the method in detail since the focus is on the national sampling frame.

> 4 The sampling frame that relies on the list of electoral precincts has been used by the “Caucasus Research Resource Center – Armenia” Foundation (CRRC-Armenia), an independent, non-partisan research center, for the Caucasus Barometer Biennial Survey that studies citizens’ views on democracy, governance, political reforms, and socio-economic developments in the region. 5 The enumeration areas are the operational geographic units for the collection and dissemination of census data and are often used as a national sampling frame for various types of socio-economic surveys.

6 Figure A.1 visually demonstrates an example of significantly changing population distribution over time to show the magnitude of the shifting population, which indicates the limitation of sampling frames with outdated population information.

7 Several attempts have been made to access the State Population Register (SPR) but failed to obtain the sampling frame based on SPR addresses. An alternative approach thus has been explored due to the time constraint.

8 A sampling frame based on the traditional grid sampling method has been explored. However, several challenges are encountered for this approach. For example, it is challenging to identify the grids' settlement type (rural or urban). Identifying administrative units, e.g., districts or villages, to which a particular grid belongs is also challenging. In addition, this strategy has other limitations, such as grid boundaries cutting buildings or settlements.

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