The impact of ‘free choice’: Family reforms of France and Belgium, a synthetic control analysis

2017 ◽  
Vol 26 (4) ◽  
pp. 340-352 ◽  
Author(s):  
Federico Podestà
Keyword(s):  
Free Choice ◽  
Control Analysis ◽  
Synthetic Control ◽  
The Impact

scholarly journals The impact of the Philadelphia beverage tax on employment: A synthetic control analysis

2021 ◽  
Vol 40 ◽  
pp. 100939
Author(s):  
Samantha Marinello ◽  
Julien Leider ◽  
Oksana Pugach ◽  
Lisa M. Powell
Keyword(s):  
Control Analysis ◽  
Synthetic Control ◽  
The Impact

scholarly journals Estimating the impact of donor programs on child mortality in low- and middle-income countries: a synthetic control analysis of child health programs funded by the United States Agency for International Development

2020 ◽  
Author(s):  
William M. Weiss ◽  
Piya Bhumika ◽  
Althea Andrus ◽  
Robert Cohen
Keyword(s):  
United States ◽  
International Development ◽  
The United States ◽  
Health Programs ◽  
Control Analysis ◽  
Synthetic Control ◽  
Middle Income ◽  
Middle Income Countries ◽  
The Impact ◽  
Low And Middle Income

Abstract Background Significant levels of funding have been provided to low- and middle-income countries for development assistance for health, with most funds coming through direct bilateral investment led by the United States and the United Kingdom. Direct attribution of impact to large scale programs funded by donors remains elusive due the difficulty of knowing what would have happened without those programs, and the lack of detailed contextual information to support causal interpretation of changes. Methods This study uses the synthetic control analysis method to estimate the impact of one donor’s funding (United States Agency for International Development, USAID) on under-five mortality across several low- and middle-income countries that received above average levels of USAID funding for maternal and child health programs between 2000 and 2016. Results In the study period (2000-16), countries with above average USAID funding had an under-fiver mortality rate lower than the synthetic control by an average of 29 deaths per 1,000 live births (year to year range of 2 – 38). This finding was stable across several sensitivity analyses. Conclusions The synthetic control method is a valuable addition to the range of approaches for quantifying the impact of large-scale health programs in low- and middle-income countries. The findings suggest that adequately funded donor programs (in this case USAID) help countries to reduce child mortality to significantly lower rates than would have occurred without those investments.

scholarly journals Estimating the Impact of Donor Programs on Child Mortality in Low- and Middle-income Countries: A Synthetic Control Analysis of Child Health Programs Funded by the United States Agency for International Development

2020 ◽  
Author(s):  
William Weiss ◽  
Bhumika Piya ◽  
Andrus Althea ◽  
Robert Cohen
Keyword(s):  
United States ◽  
International Development ◽  
The United States ◽  
Health Programs ◽  
Control Analysis ◽  
Synthetic Control ◽  
Middle Income ◽  
Middle Income Countries ◽  
The Impact ◽  
Low And Middle Income

Abstract BackgroundSignificant levels of funding have been provided to low- and middle-income countries for development assistance for health, with most funds coming through direct bilateral investment led by the United States and the United Kingdom. Direct attribution of impact to large scale programs funded by donors remains elusive due the difficulty of knowing what would have happened without those programs, and the lack of detailed contextual information to support causal interpretation of changes. MethodsThis study uses the synthetic control analysis method to estimate the impact of one donor’s funding (United States Agency for International Development, USAID) on under-five mortality across several low- and middle-income countries that received above average levels of USAID funding for maternal and child health programs between 2000 and 2016. ResultsIn the study period (2000-16), countries with above average USAID funding had an under-fiver mortality rate lower than the synthetic control by an average of 29 deaths per 1,000 live births (year to year range of 2 – 38). This finding was stable across several sensitivity analyses. ConclusionsThe synthetic control method is a valuable addition to the range of approaches for quantifying the impact of large-scale health programs in low- and middle-income countries. The findings suggest that adequately funded donor programs (in this case USAID) help countries to reduce child mortality to significantly lower rates than would have occurred without those investments.

Finally, Nebraska: A Synthetic Control Analysis of Legislative Structure

2019 ◽  
Vol 20 (1) ◽  
pp. 3-22
Author(s):  
William B. Hankins
Keyword(s):  
Control Method ◽  
Weighted Average ◽  
Sharp Decrease ◽  
Effect Estimate ◽  
Control Analysis ◽  
Synthetic Control ◽  
Per Capita ◽  
The Difference ◽  
Legislative Structure ◽  
The Impact

I estimate the impact of Nebraska’s 1937 switch from a bicameral to a unicameral legislature on state-level government expenditures. Using the synthetic control method I create a counterfactual Nebraska from a weighted average of other potential control states and compare spending in this “synthetic Nebraska” to spending in the real Nebraska. Relative to the synthetic control, Nebraska experiences a sharp decrease in expenditures per capita immediately following the switch to a unicameral legislature; however, the difference appears to diminish over time. Placebo tests show that if the change in Nebraska’s legislative structure were randomly assigned among the sample of states, and legislative structure had no real impact on spending, the likelihood of obtaining a treatment-effect estimate as large as Nebraska’s would be 0.0213. While the initial drop in expenditures per capita lends support to the theory that bicameralism, by requiring more veto players, is associated with higher levels of government spending, the fact that the difference between Nebraska and synthetic Nebraska diminishes suggests that legislators are able to circumvent this constraint.

scholarly journals Estimating the impact of donor programs on child mortality in low- and middle-income countries: a synthetic control analysis of child health programs funded by the United States Agency for International Development

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
William Weiss ◽  
Bhumika Piya ◽  
Althea Andrus ◽  
Karar Zunaid Ahsan ◽  
Robert Cohen
Keyword(s):  
International Development ◽  
Large Scale ◽  
Health Programs ◽  
Control Analysis ◽  
Synthetic Control ◽  
Middle Income ◽  
Middle Income Countries ◽  
Child Health Programs ◽  
The Impact ◽  
Low And Middle Income

Abstract Background Significant levels of funding have been provided to low- and middle-income countries for development assistance for health, with most funds coming through direct bilateral investment led by the USA and the UK. Direct attribution of impact to large-scale programs funded by donors remains elusive due the difficulty of knowing what would have happened without those programs, and the lack of detailed contextual information to support causal interpretation of changes. Methods This study uses the synthetic control analysis method to estimate the impact of one donor’s funding (United States Agency for International Development, USAID) on under-five mortality across several low- and middle-income countries that received above average levels of USAID funding for maternal and child health programs between 2000 and 2016. Results In the study period (2000–16), countries with above average USAID funding had an under-five mortality rate lower than the synthetic control by an average of 29 deaths per 1000 live births (year-to-year range of − 2 to − 38). This finding was consistent with several sensitivity analyses. Conclusions The synthetic control method is a valuable addition to the range of approaches for quantifying the impact of large-scale health programs in low- and middle-income countries. The findings suggest that adequately funded donor programs (in this case USAID) help countries to reduce child mortality to significantly lower rates than would have occurred without those investments.

Applying Synthetic Control Method to Estimate the Impact of the Lava Jato Operation on the Worldwide Governance Indicators in Brazil

2021 ◽  
pp. 2631309X2110178
Author(s):  
Eduardo Carvalho Nepomuceno Alencar ◽  
Bryant Jackson-Green
Keyword(s):  
Rule Of Law ◽  
Control Method ◽  
Synthetic Control ◽  
Synthetic Control Method ◽  
The Rule Of Law ◽  
Governance Indicators ◽  
Regulatory Quality ◽  
Legal Judgments ◽  
The Impact ◽  
Control Of Corruption

In 2014, the most prominent anti-corruption investigation in Latin America called Lava Jato, exposed a Brazilian corruption scheme with reverberations in 61 countries, resulting in legal judgments for nearly 5 billion USD in reimbursements thus far. This article applies the synthetic control method on data from 135 countries (2002–2018) to test the hypothesis that Lava Jato impacts the Worldwide Governance Indicators in Brazil. The findings reveal that Lava Jato negatively affects control of corruption, the rule of law, and regulatory quality. There are signs of possible improvement in at least the corruption and the rule of law measures. This paper brings value to the criminological body of literature, notably lacking in the Global South.

scholarly journals When is a Match Sufficient? A Score-based Balance Metric for the Synthetic Control Method

2020 ◽  
Vol 8 (1) ◽  
pp. 209-228
Author(s):  
Layla Parast ◽  
Priscillia Hunt ◽  
Beth Ann Griffin ◽  
David Powell
Keyword(s):  
Los Angeles ◽  
Control Method ◽  
Control Unit ◽  
Treated Group ◽  
Control Group ◽  
Synthetic Control ◽  
Donor Pool ◽  
Synthetic Control Method ◽  
The Mean ◽  
The Impact

AbstractIn some applications, researchers using the synthetic control method (SCM) to evaluate the effect of a policy may struggle to determine whether they have identified a “good match” between the control group and treated group. In this paper, we demonstrate the utility of the mean and maximum Absolute Standardized Mean Difference (ASMD) as a test of balance between a synthetic control unit and treated unit, and provide guidance on what constitutes a poor fit when using a synthetic control. We explore and compare other potential metrics using a simulation study. We provide an application of our proposed balance metric to the 2013 Los Angeles (LA) Firearm Study [9]. Using Uniform Crime Report data, we apply the SCM to obtain a counterfactual for the LA firearm-related crime rate based on a weighted combination of control units in a donor pool of cities. We use this counterfactual to estimate the effect of the LA Firearm Study intervention and explore the impact of changing the donor pool and pre-intervention duration period on resulting matches and estimated effects. We demonstrate how decision-making about the quality of a synthetic control can be improved by using ASMD. The mean and max ASMD clearly differentiate between poor matches and good matches. Researchers need better guidance on what is a meaningful imbalance between synthetic control and treated groups. In addition to the use of gap plots, the proposed balance metric can provide an objective way of determining fit.

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