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License information was derived automatically
This study is an impact evaluation of the KALAHI-CIDSS (KC) program. The impact evaluation's key research questions can be divided into the following four themes: 1. Socio-Economic Effects: Does KC increase household consumption? Does KC increase labor force participation? 2. Governance Effects: Does KC increase government leader responsiveness to community needs? Does KC reduce corruption and increase transparency? 3. Community Empowerment Effects: Does KC increase participation in local governance? Does KC increase collective action and contribution to local public goods? 4. Social Capital Effects: Does KC build groups and networks? In what ways are these networks applied? Does KC enhance trust? In order to isolate KC's effects, a randomized control trial evaluation design was chosen. The impact evaluation sample consists of 198 municipalities (with 33 to 69 percent poverty incidence), spread over 26 provinces and 12 regions. The 198 municipalities were paired based on similar characteristics (99 pairs) and then randomly assigned into treatment and control groups through public lotteries. The sample size is large enough to be able to detect MCC's projected eight percent change in household income as well as other smaller effects. As part of the impact evaluation, baseline quantitative data were collected in the study area from April to July 2012. The quantitative data came from 5,940 household surveys in 198 barangays (one from each municipality) and 198 barangay surveys implemented in these same barangays
This study is an impact evaluation of the KALAHI-CIDSS (KC) program. The impact evaluation's key research questions can be divided into the following four themes: Socio-Economic Effects: Does KC improve outcomes related to specific subprojects? Does it increase consumption, assets, or other facets of economic well-being? Governance Effects: Does KC increase participation in local governance and government leader responsiveness to community needs? Community Empowerment Effects: Does KC increase collective action and contribution to local public goods? In order to isolate KC's effects, a randomized control trial evaluation design was chosen. The impact evaluation sample consists of 198 municipalities (with 33 to 69 percent poverty incidence), spread over 26 provinces and 12 regions. The 198 municipalities were paired based on similar characteristics (99 pairs) and then randomly assigned into treatment and control groups through public lotteries. The sample size is large enough to be able to detect MCC's projected eight percent change in household income as well as other smaller effects.
This study is an impact evaluation of the KALAHI-CIDSS (KC) program. The impact evaluation's key research questions can be divided into the following four themes:
In order to isolate KC's effects, a randomized control trial evaluation design was chosen. The impact evaluation sample consists of 198 municipalities (with 33 to 69 percent poverty incidence), spread over 26 provinces and 12 regions. The 198 municipalities were paired based on similar characteristics (99 pairs) and then randomly assigned into treatment and control groups through public lotteries. The sample size is large enough to be able to detect MCC's projected eight percent change in household income as well as other smaller effects. As part of the impact evaluation, baseline quantitative data were collected in the study area from April to July 2012. The quantitative data came from 5,940 household surveys in 198 barangays (one from each municipality) and 198 barangay surveys implemented in these same barangays
National coverage: The sample consists of 5,940 households in 198 barangays in 198 municipalities in 26 provinces in 12 regions. The sample is representative of the KALAHI-CIDSS target population across the nation.
Individuals, households, community
The study population consists of barangays (villages) from the Philippines' poorest provinces. Survey respondent were barangay captains (village captains) and randomly selected households (30 randomly selected per barangay) from the sample of 198 barangays (villages).
Sample survey data [ssd]
The impact evaluation focuses on municipalities with between 33-69% poverty incidence. A total of 198 eligible municipalities were matched on poverty incidence, population, land area, and number of barangays. The paired municipalities were then randomly assigned into treatment and control groups through public lotteries. This resulted in the final sample of 198 municipalities (when determining the number of treatment and control municipalities, we used sample size of 30 households per municipality, ensuring an 8% (positive) change in income would be detectable at 95% significance and 80% power). The large number of municipalities included in the evaluation will provide a sufficient level of precision to estimate KC's impacts nationwide in municipalities with a poverty incidence between 33-69%. One barangay within each of the 198 municipalities participating in the evaluation was randomly chosen, with a weighted probability favoring barangays with the highest poverty rates. Within each municipality, IPA divided barangays into quintiles based on poverty and dropped the quintile with the lowest poverty incidence. For each municipality, the barangay to be surveyed for the sample was then randomly selected from the remaining barangays. Within each barangay, 30 households were randomly selected from among all households to comprise the household surveyed sample.
N/A
The baseline study included a barangay (village) questionnaire and a household questionnaire implemented in the following four different languages: Tagalog, Bisaya, Cebuano, llongo and llocano.
Household questionnaire: This questionnaire was composed of modules on education, labor income sources, household assets and amenities, expenditures, social networks, and other topics.
Barangay questionnaire: The barangay captains (village leaders were the principal respondents. The questionnaire collected data on the barangay's development projects, budget, demographics, the relationship between the existing barangay captain and its previous leadership, and other topics.
In the field, the field supervisor and data editor checked the questionnaires before the first data entry. The survey firm then conducted the second data entry in the main office and then checked the discrepancies between the first and the second data entry. The data cleaning process implemented by the survey firm included the following: 1. Naming and labelling the data 2. Checking the unique identifiers 3. Range checks and setting variable bounds 4. Check skip patterns and misisng data 5. Check logical consistency 6. Standardize string variable coding
After receiving the clean datasets from the survey firm, IPA conducted a second stage of data cleaning needed to construct variables for the analysis. This process involved carefully creating, summarizing and cross-checking key indicators.
100 percent
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This study is an impact evaluation of the KALAHI-CIDSS (KC) program. The impact evaluation's key research questions can be divided into the following four themes: 1. Socio-Economic Effects: Does KC increase household consumption? Does KC increase labor force participation? 2. Governance Effects: Does KC increase government leader responsiveness to community needs? Does KC reduce corruption and increase transparency? 3. Community Empowerment Effects: Does KC increase participation in local governance? Does KC increase collective action and contribution to local public goods? 4. Social Capital Effects: Does KC build groups and networks? In what ways are these networks applied? Does KC enhance trust? In order to isolate KC's effects, a randomized control trial evaluation design was chosen. The impact evaluation sample consists of 198 municipalities (with 33 to 69 percent poverty incidence), spread over 26 provinces and 12 regions. The 198 municipalities were paired based on similar characteristics (99 pairs) and then randomly assigned into treatment and control groups through public lotteries. The sample size is large enough to be able to detect MCC's projected eight percent change in household income as well as other smaller effects. As part of the impact evaluation, baseline quantitative data were collected in the study area from April to July 2012. The quantitative data came from 5,940 household surveys in 198 barangays (one from each municipality) and 198 barangay surveys implemented in these same barangays