Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Effect of fiscal census program on extensive margin of tax compliance: our baseline survey showed that 13% of eligible property owners paid the property tax in 2018. With 97 sections in T, and 97 in C, 397 properties per section on average (total number of plots in T and C sections: 77,208), and based on an intra cluster correlation of 0.08 (as observed in baseline data) and a power of 0.80, we can detect an effect of 4 percentage points (from to 13 to 17%) of the program on tax compliance . This is realistic considering the existing literature on property tax. This minimum detectable effect is also sufficient from a policy point of view. Indeed, given the significant cost of modernizing the tax system, an effect below 4 percentage points would not be cost effective. We use the following stata command: “clustersampsi,binomial detectabledifference p1(0.13) m(397) k(97) rho(0.08)”
Effect of rules vs discretion on accuracy of tax assessment: In the baseline data, for 22% of cases property value implicitly assessed by the tax administration based on the amount of tax paid (as declared by the owner) is within 30% of the “objective” annual rental property value assessed by a real estate expert. With 48 sections in the “Rule” treatment arm and 49 sections in the “Discretion” treatment arm, with a survey sample size of 20 properties in each section, assuming a power of 0.80 and based on an intra-cluster correlation of 0.01 (observed in the baseline data), we can detect a difference of 6 percentage points (from 22 to 28%) in the proportion of “correctly assessed” properties between the two assessment regimes.
Effect of fiscal census program on local governance outcomes: This will be measured using taxpayer survey data, clustered at the section level. Our baseline survey showed that 46% of property owners were in touch with a representative of local government (municipality, neighborhood delegate) in the past 6 months. Assuming an intra-class correlation of 0.04 (from baseline data), and a power of 0.80, with 97 sections in T and 97 in C, with a survey sample size of 20 respondents in each section, we can detect an effect of 6 percentage points (increase from 46 to 52%) on taxpayer interactions with local administrations. This corresponds to a 13% increase, which we believe is realistic considering the literature. We use the following stata command: “clustersampsi,binomial detectabledifference p1(0.46) m(20) k(97) rho(0.04)”