# **1 Introduction**

The national sampling frame, a list of primary sampling units (PSUs) such as enumeration areas from a recent census, is essential for collecting reliable data. This is a global challenge in conducting representative surveys necessary for high-quality research and policy analysis with minimum bias in many developing countries, especially in conflict-affected nations. Most countries, including the Republic of Armenia, have national sampling frames based on census enumeration areas developed for past population censuses. However, the census frames are often outdated, non-digital, incomplete, and restrictive or hardly accessible to parties other than local governmental organizations, such as researchers, academics, and international organizations. These issues are particularly severe in Armenia as the country recently experienced a large-scale refugee crisis and dramatic change in population distribution across regions over time due to the Nagorno-Karabakh Conflict.<sup>2</sup> The lack of accessible and workable population sampling frames due to these challenges undermines the initiatives and efforts to collect surveys for statistical, policy, and research purposes.

This paper first systematically assesses the existing sampling frames in the country, focusing on those that leverage census settlements—villages in rural areas, towns in urban areas, districts in the capital city, Yerevan—and electoral precincts as PSUs. The strengths and limitations of these sampling frames and potential solutions to those challenges and drawbacks have also been discussed. To overcome the limitations of those existing and accessible national sampling frames in the country, this paper thus constructs an innovative national sampling frame based on pre-census enumeration areas (pre-EAs) using a novel approach and the most recent population estimates.

The primary challenge with using census settlements as PSUs is the relatively few and large-sized PSUs, making the sampling extremely challenging and costly even in a stratified two-stage cluster sampling design via increasing the monetary and non-monetary cost of household listing. Especially, in this frame, Yerevan is split into only 12 districts with large populations and extensive territories. All districts will likely be selected in the first stage of the two-stage stratified cluster sampling design according to the probability proportional to size (PPS) method. In the second stage, thus, the survey conductor is likely to conduct the household listing, the ideal and preferred approach for the second stage of the two-stage sampling, in the entire Yerevan, which would take the costs and efforts required in the Census. So, under this sampling frame, household listing is almost impossible for household surveys.<sup>3</sup> Electoral precincts, on the other hand, offer relatively

> 2 Armenia and Azerbaijan have been in a territorial conflict over the Nagorno-Karabakh area which has a majority ethnic-Armenian population but was controlled by Azerbaijan before the collapse of the Soviet Union in the late 1980s. Following the collapse of the Soviet Union, the local parliament of Nagorno-Karabakh voted to become part of Armenia, which led to an ethnic clash between the two countries. Then the first Nagorno-Karabakh War started and ended in 1994 with an agreement stating that the area remains part of Azerbaijan but run by a self-declared republic of ethnic Armenians, backed by the Armenian government. However, Azerbaijan regained power over the area in 2020, and more than half of the estimated 120,000 ethnic Armenians fled from Nagorno-Karabakh to Armenia since the ceasefire (https://www.bbc.com/news/world-europe-66852070).

> 3 Although it is not ideal and not encouraged, one might consider using a random walk approach to select households in the second stage of the two-stage sampling as a last resort under pressing constraints. However, sample households will likely be concentrated in particular areas or demographic groups under this approach if the random walk is not properly executed, which happens most of the time, because the enumerators can walk around the starting point. Listing the households is preferred over random walk but requires time and financial resources. Survey conductors tend to use random walks if subject to those constraints, like the Listening to Armenia Survey. If the starting point and skipping steps are randomly selected, the random walk approach would be essentially the same as random sampling with equal probabilities. However, households selected via random walk can be concentrated around certain areas, leaving out most PSU territories. Consequently, representativeness suffers, and only a subpopulation might be sampled. Due to these and other issues of the random walk method that can introduce serious biases, it is

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