Table 7: Estimation results of regressions on household poverty status

||||Poverty|status (1 =|poor, 0 = n|on-poor)||||
|---|---|---|---|---|---|---|---|---|---|
||(1)<br>$2.15|(2)<br>$2.15|(3)<br>$2.15|(4)<br>$3.65|(5)<br>$3.65|(6)<br>$3.65|(7)<br>$6.85|(8)<br>$6.85|(9)<br>$6.85|
|**Panel A: DOU**||||||||||
|Urban center<br>Urban cluster|-0.205***<br>(0.005)<br>-0.047***|-0.113***<br>(0.006)<br>-0.016***|-0.067***<br>(0.006)<br>0.002|-0.334***<br>(0.006)<br>-0.077***|-0.196***<br>(0.006)<br>-0.031***|-0.131***<br>(0.006)<br>-0.008|-0.235***<br>(0.005)<br>-0.048***|-0.129***<br>(0.005)<br>-0.015***|-0.094***<br>(0.005)<br>-0.002|
||(0.006)|(0.006)|(0.006)|(0.006)|(0.005)|(0.005)|(0.003)|(0.003)|(0.003)|
|**Panel B: DB**||||||||||
|Core|-0.147***|-0.073***|-0.039***|-0.212***|-0.099***|-0.047***|-0.154***|-0.070***|-0.043***|
||(0.006)|(0.006)|(0.007)|(0.006)|(0.006)|(0.006)|(0.004)|(0.004)|(0.004)|
|Suburb|-0.010|0.012*|0.018**|-0.014**|0.018***|0.027***|-0.020***|0.002|0.007*|
||(0.007)|(0.007)|(0.007)|(0.007)|(0.006)|(0.006)|(0.004)|(0.004)|(0.004)|
|Town|0.034***<br>(0.007)|0.043***<br>(0.007)|0.039***<br>(0.007)|0.043***<br>(0.007)|0.054***<br>(0.007)|0.048***<br>(0.006)|0.028***<br>(0.004)|0.033***<br>(0.004)|0.030***<br>(0.004)|
|Country FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Demographic|No|Yes|Yes|No|Yes|Yes|No|Yes|Yes|
|Education|No|Yes|Yes|No|Yes|Yes|No|Yes|Yes|
|Employment|No|No|Yes|No|No|Yes|No|No|Yes|
|Panel A Adj.R<sup>2</sup>|0.104|0.164|0.173|0.160|0.263|0.276|0.138|0.249|0.257|
|Panel B Adj.R<sup>2</sup>|0.100|0.167|0.177|0.135|0.254|0.272|0.119|0.244|0.253|
|Nr. of countries|16|16|16|16|16|16|16|16|16|
|Nr. of hh|134872|134872|134872|134872|134872|134872|134872|134872|134872|

Source: International Urban Poverty Database. Note: *** p < 0.01, ** p < 0.05, *** p < 0.1. Robust standard errors in parentheses. WorldPop 250m is used for the DOU and DB method. The dependent variable is a dummy variable taking the value 1 if a household’s per capita expenditure expressed in PPP and spatially deflated falls below the poverty line. The baseline category is “Rural” in all specifications in Panel A, and “Other rural” in all specifications in Panel B. Demographic control variables include household size and household head’s age, sex, and marital status. Education is a categorical control variable that summarizes the education of the household head in seven categories. Employment is a categorical control variable that summarizes the household head’s labor status and employment sector.

areas. Conversely, 13 percent of the urban non-poor population and 23 percent of the urban poor households are reclassified into the rural non-poor and rural poor populations, respectively. The scale of rural-to-urban reclassification is even more significant when transitioning from the official urban definitions to the DB approach (Panel B), with 47 percent of the non-poor and 56 percent of the poor being reclassified. It is worth noting that spatial deflation primarily reduces poverty in rural areas due to their relatively low prices.

# **5.4 Additional analyses**

In this sub-section, we present additional analyses to demonstrate the practical applications of our approach in analyzing other key outcomes, including spatial inequality, non-monetary poverty, and employment.

## _Spatial inequality_

In addition to poverty, the urban and rural dimensions of inequality are a crucial factor in assessing welfare distributions in low- and middle-income countries. By utilizing household-level consumption expenditures from our dataset, we are able to measure inequality using various standard indicators. Our focus lies on the Theil index, which is calculated based on per capita household consumption expenditures and can be easily decomposed into within-group and between-group components.<sup>28</sup>

> 28Similar results are obtained based on another inequality indicator, such as Gini Coefficients (results available upon request).

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