# **1 Introduction and Background**

Monitoring progress in poverty reduction is constrained by the limited availability of household expenditure or income surveys. According to Serajuddin et al. 2015, around 60 countries had either zero or only one household survey for monitoring poverty in a 10-year period between 2002 and 2011, and additional 20 countries had two surveys in the 10-year period but the surveys were not carried out regularly. According to the International Monetary Fund’s General Dissemination Data System (GDDS), a country needs to have national poverty estimates every three to five years. In this sense, nearly 80 countries or half the countries included in the World Bank’s database suffered limited availability of household survey data for estimating poverty indicators to some degree. In the Sub-Saharan Africa region, the situation is even more serious. More than 80 percent of countries in the region did not have regular household income or expenditure surveys to produce national poverty estimates every five years.

The limited availability of poverty data restricts our ability to monitor progress toward the goals of ending extreme poverty and promoting shared prosperity – the goals that the World Bank Group committed itself to achieving. This is particularly the case for monitoring of the latter. The shared prosperity indicator is the growth rate of the mean income or expenditure of the poorest 40 percent of population over a period of roughly 5 years. Therefore, if a country does not have a household expenditure or income survey every five years or less, it is difficult to regularly estimate the shared prosperity index.

One of the main reasons why data are so limited is that collecting household expenditure or income data is costly and time-consuming if the data are collected via traditional face-to-face interviews. To estimate the prevalence of poverty, a household survey needs to collect at minimum 50 food items, each of which needs to include different sources of consumption, such as purchases, gifts, and own production. Completing an interview of a household survey often requires more than one hour, and worse, collection of such data often requires multiple visits by enumerators. As a result, it is not rare to see that a country spent more than two million US dollars for carrying out a household income or expenditure survey.

A recent surge of telephone coverage even in low income countries gives us hope that the use of telephone interviews can save time and costs of data collection significantly. Telephone interviews eliminate transportation and lodging costs, which usually comprise a large share of costs of data collection via the face-to-face interviews. The cost-effectiveness of telephone interviews can be further enhanced using automatic data collection via Short Message Service (SMS) or Interactive Voice Response (IVR).<sup>1</sup> However, such telephone data collections are not flawless. Telephone surveys often have problems in terms of sampling. Since ownership of landlines or even cell phones is skewed toward the richer segment of population, responses to telephone interviews are often not nationally representative. How to ensure representativeness of the sample is therefore a challenge for telephone surveys. Another challenge is that it is difficult to have a long interview via telephone, but as mentioned above, collection of consumption or income data takes easily

> 1 SMS stands for Short Message Service and means the text messaging service component of mobile phones that allows exchange of short messages between devices. Messages are delivered using “store and forward” where messages are first sent to a SMS Center before delivering the text to the recipient. IVR stands for Interactive Voice Response and means a technology that allows a computer to interact with humans through the use of voice and dial tones through the keypad.

2