# **Table 2: Hierarchy and Information**

**Dependent Variable:  A binary indicator of whether respondent doesn't know in columns (1) and (2); Z-score of errors across all policy domains in columns (3) to (10) OLS Estimates**

**Standard Errors: Clustered at the district government-sector level**

||**(1) Don't know**<br>**Unconditional**|**(2) Don't know**<br>**Conditional**|**(3) Unconditional**<br>**Decentralized**|**(4) Unconditional**<br>**Manager**|**(5) Unconditional**<br>**Hierarchies**|**(6) Sector FEs**|**(7) District**<br>**government FEs**|**(8) Indicator FEs **|**(9) Percentile FEs**|**(10) Individual**<br>**Characteristics**|
|---|---|---|---|---|---|---|---|---|---|---|
|**District Government [Yes=1]**|-0.17|-0.17|-0.27||-0.27|-0.28|-0.30|-0.31|-0.31|-0.33|
||[0.034]|[0.033]|[0.084]||[0.084]|[0.084]|[0.086]|[0.087]|[0.087]|[0.087]|
|**Manager [Yes=1]**|0.011|0.0040||0.011|0.023|0.020|0.014|0.016|0.015|0.034|
||[0.031]|[0.029]||[0.066]|[0.066]|[0.067]|[0.065]|[0.066]|[0.066]|[0.069]|
|**Sector fixed effects**|No|Yes|No|No|No|Yes|Yes|Yes|Yes|Yes|
|**District government fixed effects**|No|Yes|No|No|No|No|Yes|Yes|Yes|Yes|
|**Indicator fixed effects**|No|Yes|No|No|No|No|No|Yes|Yes|Yes|
|**Percentile fixed effects**|No|Yes|No|No|No|No|No|No|Yes|Yes|
|**Individual controls**|No|Yes|No|No|No|No|No|No|No|Yes|
|**Adjusted R-squared**|0.022|0.13|0.012|-0.00066|0.012|0.0099|0.059|0.067|0.072|0.069|
|**Observations [clusters]**|2144 [98]|2144 [98]|1455 [92]|1455 [92]|1455 [92]|1455 [92]|1455 [92]|1455 [92]|1455 [92]|1455 [92]|
|**Central government respondents [percentage]**|594 [67%]|594 [67%]|429 [62%]|429 [62%]|429 [62%]|429 [62%]|429 [62%]|429 [62%]|429 [62%]|429 [62%]|
|**Districtgovernment respondents[percentage]**|297[33%]|297[33%]|258[38%]|258[38%]|258[38%]|258[38%]|258[38%]|258[38%]|258[38%]|258[38%]|

**Notes:** Clustered standard errors are in parentheses.  Standard errors clustered at the district government-sector interacted level.  All columns report OLS estimates.  The unit of analysis in all columns is the claim.  The sample used for the analysis is the set of respondents that make claims about the same districts.  The dependent variable is a binary indicator for whether the respondent could not provide a claim in columns (1) and (2); the z-score of absolute error across all policy domain items in columns (3) to (12).  Sector fixed effects are indicators for whether the claim is within an agriculture, education, health, revenue, or trade organization.  Percentile fixed effects are indicators for the 75th, 50th or 25th percentile for the respective indicator for the respective region.  District government fixed effects identify the district that the respondent is making claims about.   Indicator fixed effects control for the service delivery indicator within which the claim is made.  Manager is equal to one if the claim is from a director.  Individual characteristics included in the specification:  tenure in the civil service of the respondent making the claim;  tenure in the position; tenure in the organization;  an indicator for whether the respondent is female; an indicator for whether the respondent holds an undergraduate degree; an indicator for whether the respondent holds a masters degree. Figures are rounded to two significant figures.