Combining the effects that _Voice_ has on the demand for, and supply of sanitation, we see that equilibrium access to and use of sanitation services in developing countries positively depends on voice and accountability and other factors— _s_<sup>_∗_</sup> = _s_ ( _v, Z_ ) _, ∂ s_<sup>_∗_</sup> _/∂ v >_ 0, where _s_<sup>_∗_</sup> is the observed amount of sanitation services provided in a country. In this simple formulation, _Voice_ can increase sanitation access through the demand side by households, the supply side by government, and/or other factors.

# 4. DATA AND ESTIMATION METHODS

This section describes the various layers of the country-level analyses of the influence of _Voice_ on access to sanitation, discusses key variables employed, as well as the empirical strategies implemented to identify the causal effect of _Voice_ on access to sanitation. Our analysis focuses on measures of access to sanitation, exploiting variations in cross-country data. We estimate the effect of _voice_ on: (i) overall access to sanitation, (ii) access to sanitation in rural and urban areas, and (iii) closing the rural/urban gap in access to sanitation. The first sub-section describes the data while the second sub-section briefly describes our estimation methods and empirical strategy.

4.1 DATA AND DESCRIPTIVE STATISTICS In this section, we present descriptions and data sources for our main variables. We utilize data from 73 developing countries to study the effect of voice and accountability on access to sanitation. We measure our dependent variable, the access to sanitation ( _S_ ) in four different ways: (1) the proportion of the entire population using basic sanitation ( _St_ ), (2) proportion of rural population using basic sanitation ( _Sr_ ), (3) proportion of urban population using basic sanitation services ( _Su_ ), and (4) the rural-urban gap in access to sanitation ( _Sg_ ). The data for _S_ and its various components is from _World Development Indicators (2021)_ . Our main explanatory variable is the institutional variable, voice and accountability ( _Voice_ ). This variable captures perceptions of the extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. We employ the standard measure of freedom of expression, of association and free media as our measure of _Voice_ . The standard measure of this variable ranges from -2.5 to 2.5 with higher values being associated with better outcomes and hence, higher levels of quality _Voice_ . We use this index because it provides the most up-to-date measure of broad institutions relevant to the time period we consider. The data on _Voice_ comes from the _Worldwide Governance Indicators_ constructed by Kaufmann, Kraay, and Mastruzzi (2011).

We include potentially important control variables in our empirical estimation. In particular, we include GDP per capita and population density. GDP per capita is included as a measure of income level as well as a proxy for overall economic development in each country. Per capita GDP is measure is real terms (constant 2015 US$). We expect a positive relationship between access to sanitation and the level of per capita income across countries. We include population density in the analysis to control for possible scale or scope economies effects. The relationship between population density and access to sanitation can be positive or negative. A positive relationship may arise because higher population density could mean lower administrative costs as well as scale economies and thus translate lower cost of access to improved sanitation facilities for a larger segment of the population (Gopalan and Rajan, 2016). On the other hand, sanitation is a rival good at least in low and lower-middle income countries, hence, higher population density could be associated with lower access to sanitation as a share of the population. Data on per capita GDP and population density were obtained from the World Development Indicators (World Bank, 2021). Controlling for these factors may help with minimizing specification errors.

severity of the sanitation problem.

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