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{
    "original_study": {
        "claim": {
            "hypothesis": "ACT [artemisinin combination therapies] subsidies induce take-up of ACT",
            "hypothesis_location": "discussed in the abstract and introduction",
            "statement": "a very high subsidy (such as the one under consideration by the international community) dramatically increases access, but nearly one-half of subsidized pills go to patients with-out malaria. The coefficient for “Any ACT subsidy” is 0.187 with robust standard errors clustered at the household level of 0.038, significant at the 1 percent level.",
            "statement_location": "Table 2, column 1, row 1.",
            "study_type": "Experimental" 
        },

        "data": { 
            "source": "NA",
            "wave_or_subset": "NA",
            "sample_size": "631",
            "unit_of_analysis": "illness episode",
            "access_details": "The experimental data are presumably stored by IPAKenya field officers who collected the data or one of the authors. There is a note on the first page that there are additional materials at: http://dx.doi.org/10.1257/aer.20130267, but no mention if the repository contains the actual data or the code.",
            "notes": "The study was conceived and implemented in 2008–2009. The study to included three subsidy levels 80, 88, and 92 percent. The experiment was conducted in the districts of Busia, Mumias, and Samia in Western Kenya between May and December of 2009. If more than one household member got sick simultaneously, the authors included all concurrent first episodes, and therefore clustered the standard errors in all illness episode regressions at the household level."
        },

        "method": {
            "description": "The study evaluates the impact of randomized subsidies for artemisinin combination therapies (ACTs) on ttake-up of ACTs, using experimental data and regression analysis to estimate effects on ACT access and targeting.",
            "steps": "1. The authors selected four rural market centers in Western Kenya and partnered with one drug shop in each; they sampled all households within a 4-kilometer catchment radius, excluding areas near health facilities. \n2. They administered a baseline household survey and distributed two vouchers for artemisinin-based combination therapies (ACTs). \n3. They randomly assigned households using a computerized algorithm (stratified by drug shop, distance quartile, and presence of children) to one of two groups: (a) No Subsidy: Unsubsidized ACTs at the market price. (b) ACT Subsidy: ACTs discounted at 80%, 88%, or 92% subsidy levels. \n4. Then, they recorded voucher redemptions and treatment details for illness episodes at participating drug shops over a four-month period. \n5. Finally, they conducted an endline household survey approximately four months after baseline to document illness episodes, treatment-seeking behavior, and medication use. \n6. Having all the data, they estimated the causal effect of ACT subsidies on ACT access using OLS regressions with household-clustered robust standard errors and strata fixed effects.",
            "models": "ordinary least squares regression",
            "outcome_variable": "ACT access",
            "independent_variables": "pooled dummies for ACT subsidy levels (80%, 88%, 92%)",
            "control_variables": "household head age and a full set of strata dummies (drug shop, household’s distance to the drug shop (in quartiles), presence of children in the household)",
            "tools_software": "not stated"
        },
        "results": {
            "summary": "The coefficient for “Any ACT subsidy” is 0.187 with robust standard errors clustered at the household level of 0.038, significant at the 1 percent level.",
            "numerical_results": [ 
                {
                    "outcome_name": "ACT access",
                    "value": "0.187",
                    "unit": "NA",
                    "effect_size": "not stated",
                    "confidence_interval": {
                        "lower": "not stated",
                        "upper": "not stated",
                        "level": "not stated"
                    },
                    "p_value": "<0.01",
                    "statistical_significance": "true",
                    "direction": "positive"
                }
            ]
        },
       
        "metadata": {
            "original_paper_id": "http://dx.doi.org/10.1257/aer.20130267",
            "original_paper_title": "Price Subsidies, Diagnostic Tests, and Targeting of Malaria Treatment: Evidence from a Randomized Controlled Trial.",
            "original_paper_code": "not stated",
            "original_paper_data": "not stated"
        }
    }
}