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Field
Trial Status
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Before
on_going
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After
completed
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Last Published
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Before
March 29, 2017 04:45 PM
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After
May 25, 2020 07:52 AM
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Intervention (Public)
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Before
The primary intervention randomly assigns certain neighborhoods to receive an on-the-ground property and rental tax collection program, aided by tablet computers and handheld thermal receipt printers. This study will attempt to measure the impact of the program on citizen beliefs about the government and citizen efforts to hold the government accountable. Specifically, the study will exploit random variation in taxes paid to examine the theorized link between taxation and civic engagement. Additionally, two cross-randomized interventions will be used to study how to limit bribe taking among tax collectors administering this new program. First, a collector monitoring (“audit”) intervention will be randomly assigned among neighborhoods that receive the on-the-ground taxation program. Second, a citizen-empowerment information intervention will be randomly assigned among all neighborhoods in the city.
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After
The primary intervention randomly assigns certain neighborhoods to receive an on-the-ground property tax collection program, aided by tablet computers and handheld thermal receipt printers. This study will attempt to measure the impact of the program on citizen beliefs about the government and citizen efforts to hold the government accountable. Specifically, the study will exploit random variation in taxes paid to examine the theorized link between taxation and civic engagement. Additionally, two cross-randomized interventions will be used to study how to limit bribe taking among tax collectors administering this new program. First, a collector monitoring (“audit”) intervention will be randomly assigned among neighborhoods that receive the on-the-ground taxation program. Second, a citizen-empowerment information intervention will be randomly assigned among all neighborhoods in the city.
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Field
Primary Outcomes (End Points)
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Before
For the main intervention (random assignment of on-the-ground tax collection), the main outcome variables are as follows:
- Tax receipts and government revenues: measured using official government data.
- Citizen views about the government: measured with survey questions, implicit-association tests, and behavioral games.
- Citizen expectations of the government: measured with survey questions.
- Citizen engagement in politics and efforts to hold the government accountable: measured with survey questions, feedback experiments, public meeting experiments (to determine show-up rates), election turnout data (if accessible).
For the cross-randomized interventions aimed at reducing corruption among tax collectors, outcome variables are as follows:
- Availability of valid receipt: e.g. if a participant has a printed receipt from the program.
- Discrepancies between citizen receipts and official program records: e.g. if a tax collector issues a receipt but does not submit this money to the tax ministry.
- Discrepancies between the amounts citizens report paying and official program data: e.g. if a household reports paying X (without regard to whether the household has a receipt) and in the official tax ministry data, the reported amount is X-b.
- The amount citizens report paying, including bribe amounts less than the official tax.
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After
For the main intervention (random assignment of on-the-ground tax collection), the main outcome variables are as follows:
- Tax receipts and government revenues: measured using official government data.
- Citizen views about the provincial government: measured with survey questions
- Citizen participation with provincial government: measured by attendance at townhall and submission of government evaluations
For the cross-randomized interventions aimed at reducing corruption among tax collectors, outcome variables are as follows:
- Availability of valid receipt: e.g. if a participant has a printed receipt from the program.
- Discrepancies between citizen receipts and official program records: e.g. if a tax collector issues a receipt but does not submit this money to the tax ministry.
- Discrepancies between the amounts citizens report paying and official program data:
- The amount citizens report paying, including bribe amounts less than the official tax.
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Primary Outcomes (Explanation)
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Before
For the main intervention, variables will be constructed as follows:
- Tax receipts and government revenues: these outcomes will simply be taken from official government data.
- Citizen views about the government
o Survey questions: standardized indices of underlying survey questions will be constructed and used as the principal outcomes of interest. Individual survey questions will be examined to explore mechanisms and heterogeneity, but only in the case where results for other individual questions are reported.
o Implicit-association tests: the standard D-score from the psychology literature will be reported.
o Behavioral games: the standard “amount sent” to the player 2 will be used as the dependent variable.
- Citizen expectations of the government
o Survey questions. Standardized indices of underlying survey questions will be constructed and used as the principal outcome of interest. Individual survey questions will be examined to explore mechanisms and heterogeneity, but only in the case where results for other individual questions are reported. Vignette-style “fill in the outcome” questions will also be used.
- Citizen engagement in politics and efforts to hold the government accountable
o Survey questions: standardized indices of underlying survey questions will be constructed and used as the principal outcome of interest. Individual survey questions will be examined to explore mechanisms and heterogeneity, but only in the case where results for other individual questions are reported. Additionally, a survey-based quiz about the government will be used to measure citizen knowledge of the government. Finally, a separate survey module will be administered in which participants can choose to continue receiving information about the government if they so desire; the decision to continue is taken as an interest in engaging more in politics.
o Government feedback experiments: whether or not individuals choose to send feedback to the government via several channels created by the program. Indicator variables will be calculated whether a citizen makes the effort to provide feedback. When possible more continuous measures will be defined using the distance from an individual’s house to the location where one deposits a feedback form for example.
o Public meeting experiments: whether or not an individual shows up will determine a dummy variable outcome; again, analysis with this variable will condition on the distance from a person’s house to the location.
o Election data: a dummy variable will be defined if an individual votes in the December 2016 elections (likely to be postponed until sometime in 2017) again, analysis with this variable will condition on the distance from a person’s house to the location. If official polling station data are unavailable, self-reports may be used.
For the cross-randomized interventions, outcome variables will be constructed as follows:
- Availability of valid receipt: an indicator that equals 1 if a citizen possesses a valid receipt, conditional on reporting having paid the tax.
- Discrepancies between citizen receipts and official program data: an indicator that equals 1 if a household reported having paid the tax but there is no record in the official tax ministry data.
- Discrepancies between the amounts citizens report paying and official program data: the difference between the amount citizens report paying and the amount recorded in the official data of the tax ministry. This quantity will be examined as well as an indicator variable that equals 1 if the above quantity is not zero.
- The precise amount citizens report paying: this will just be an integer measured in Congolese Francs. In addition to self reports, two other more subtle elicitation methods will be used since the quantity of the bribe is potentially sensitive information.
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After
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Randomization Method
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Before
The random assignment of treatments to polygons will be conducted in STATA using a specified seed. Additionally, randomized selection for different survey modules will occur using built-in randomization software in the SurveyODK survey program. Random assignment of tax collectors to polygons and to partners will be conducted in R using a specified seed.
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After
The random assignment of tax collection treatments to polygons will be conducted in Stata using a specified seed.
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Planned Number of Observations
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Before
Estimated sample sizes are 2720 individuals for survey-based variables and 1360 individuals for experimental variables.
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After
The midline sample will have nearly 30,000 observations. The endline sample will have nearly 3000 observations.
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Sample size (or number of clusters) by treatment arms
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Before
On-the-ground tax collection program (main treatment): 1600
Old tax collection program (control): 1120
Information treatment: 1360
Audit treatment: 800
In other words, within the taxed polygons there is a 2x2 matrix with the following combinations of treatments: audit + information, audit + no information, no audit + information, no audit + no information. Each of these cells has 400 units. Half of the control units also receive the information treatment.
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After
The distribution of sub-treatments across clusters (neighborhoods) is shown below. The tax program includes both the Audit and No Audit columns in the below, meaning that 253 of 431 neighborhoods were assigned to the Tax treatment.
"Audit" "No Audit" "Control"
Info 65 62 88
No Info 60 66 90
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Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
The pre-analysis plan will specify the full set of power estimates based on the sampclus command in STATA, Optimal Design, and simulations in R.
In short, power calculations were conducted using data gathered in Kananga in previous years. I do not have access to the exact outcome variables I plan to collect. However, I do have several analogs that were conducted for other research in Kananga in past years. Specifically, a version of the Random Allocation Game with the Government as the Player 2 was administered in 2013-2014, which is one of the anticipated measures of views of the government. The outcome is the amount allocated to the second player, an integer between 0 and 3000 Congolese Francs (CF). Second, in past years, information on trust in the provincial government was collected; this is a reasonable approximation of some of the survey-based outcome variables I aim to use gauging citizens’ views of the government. This question uses an ordinal 1-5 Likert-style scale, increasing in trust. The data are on the individual level. The standard deviation for the RAG outcome is 441.25 (CF), and the standard deviation for the trust survey outcome is 1.05. Standard errors are clustered by polygon.
In the simplest specification, regressing the outcome on a treatment dummy, the estimated MDE with power of 0.8 for the RAG outcome is 0.201 and 0.204 for the trust questions. In a regression that includes dummies for all four treatment cells (audit + information, etc), MDEs on the coefficients of interest range from 0.26 to 0.29.
For the corruption outcomes, the only available proxy for the anticipated dependent variables is a binary bribe indicator taken from surveys with motorbike drivers at tolls in Kananga (in a separate experiment with Otis Reid also currently underway). The standard deviation for this variable is 0.47. According to this estimated dependent variable and a power level of 0.80, the MDE for the coefficient on dummies for each treatment cell of interest (audit + information, etc) range from 0.185 to 0.191. Again, see the Pre-Analysis Plan for more details on these power calculations.
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After
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Intervention (Hidden)
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Before
The primary intervention is the on-the-ground tax collection program, which is enabled by the use of tablets and handheld printers. But the intervention is more properly understood as the fact of having tax collectors going door to door. In control neighborhoods, collectors will not do this. Rather, tax payers are themselves required by law to go to the tax ministry to pay property and rental taxes. This is how all tax collection for these taxes occurred in the past. Sampling will be conducted with 431 polygons drawn on a satellite map of the city of Kananga. Treatment and control are defined on the level of these polygons.
The audit intervention involves independent enumerators conducting audits in randomly selected polygons that receive the on-the-ground tax collection program. Several aggregate statistics will be made public at the tax ministry, and particular to tax ministry leadership who have threatened sanctions for under-performing collectors. These statistics include: the number of differences between the amount that people on the ground claim to have paid and the amount officially recorded in the government’s data; the number of households that report receiving multiple visits from tax collectors (beyond the initial census visit during which no money is collected); the number of cases in which households say they received handwritten instead of printed receipts.
The information intervention consists of distributing fliers that show the price of the tax and an example of a printed receipt. This intervention will also be randomly assigned at the polygon level but among all polygons in the city (those that receive the on-the-ground program and those that do not). Control polygons will also receive fliers but these will contain more generic information: that there will be a tax campaign, without mentioning the specific price of the tax or showing an example printed receipt.
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After
The primary intervention is the on-the-ground tax collection program, which is enabled by the use of tablets and handheld printers. But the intervention is more properly understood as the fact of having tax collectors going door to door. In control neighborhoods, collectors will not do this. Rather, tax payers are themselves required by law to go to the tax ministry to pay property and rental taxes. This is how all tax collection for these taxes occurred in the past. Sampling will be conducted with 431 polygons drawn on a satellite map of the city of Kananga. Treatment and control are defined on the level of these polygons.
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