ArCo: An R package to Estimate Artificial Counterfactuals

Fonseca, Yuri; Masini, Ricardo; Medeiros, Marcelo C.; Vasconcelos, Gabriel

doi:10.32614/rj-2018-016

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…The post-treatment dyanmics of both series largely mimics that of the SCM plots, lending credence to our SCM findings, and their interpretation. 9 We trial multiple ArCo specifications (R package: ArCo) based on examples provided by Fonseca, Masini, Medeiros, and Vasconcelos (2018). The observed trends and results are consistent across all specifications.…”

Section: Robustness Of Synthetic New Hampshire: Arco Estimationmentioning

confidence: 83%

The effect of interest rate caps on bankruptcy: Synthetic control evidence from recent payday lending bans

Dasgupta

Mason

2020

Journal of Banking & Finance

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Citing consumer protection concerns, New Hampshire-along with three other states-recently banned payday lending by implementing an APR cap on small loans. New Hampshire presents a compelling quasi-experiment: its neighbors already had a payday loan ban in place. Hence, New Hampshire consumers were completely shut out of the storefront payday loan market. We perform a synthetic control analysis for all four of the recently-banning states. Our results show that, on the aggregate, bankruptcies are largely unaffected by the bans. Our New Hampshire results are characterized by an initial rise in bankruptcies after the ban, followed by a fall. This is consistent with the notion that payday bans hurt credit-constrained consumers in the short-run, but could help them in the long-run. We also analyze survey data of payday borrowers and find that while bankruptcies are unaffected, consumers substitute toward paying their credit card bills late and using pawnshops.

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Section: Robustness Of Synthetic New Hampshire: Arco Estimationmentioning

confidence: 83%

The effect of interest rate caps on bankruptcy: Synthetic control evidence from recent payday lending bans

Dasgupta

Mason

2020

Journal of Banking & Finance

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“…As the SC method the application of the AC method is based on two key assumptions (Fonseca et al, 2018 ): The control units are not affected by the intervention (the crisis) and The data are trend stationary. …”

Section: Methodsmentioning

confidence: 99%

“…It is characterized by a rapid rise in life expectancy thanks, above all, to a significant reduction in cardiovascular mortality (the so-called cardiovascular revolution). Third, Fonseca et al ( 2018 ) suggest using at least 40–50 observations when applying the AC method. However, since our results may depend on the length of the time series employed in the procedure, we resolved to repeat our tests by also using the shorter period 1990–2019.…”

Section: Methodsmentioning

confidence: 99%

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The Effect of the Great Recession on Italian Life Expectancy

Salinari

Benassi

Carboni

2023

Popul Res Policy Rev

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The 2008 economic crisis, also called the Great Recession, produced only a moderate rise in unemployment in Italy, but the consequences for public debt management were far more serious. Italy makes for a good case study for evaluating the effect on life expectancy at birth of the cost containment program in the health care system, implemented after the crisis began. To this end we employed the Artificial Control method using the data from the Human Mortality Database to assess the causal effect of the 2008 economic crisis on the subsequent evolution of life expectancy at birth (until 2019, before the onset of the COVID-19 pandemic). Our analysis identifies a significant deceleration in the progression of Italian life expectancy. Ten years after the onset of the crisis, Italy appears to have lost almost 1 year of life expectancy with respect to what would have been expected had the crisis never happened.

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“… 1 Carvalho, Masini, and Medeiros (2018) propose statistical inference only for the average treatment effect. However, Fonseca et al (2018) point out that estimation of the covariance matrix is practically challenging for some choices of robust estimators. …”

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confidence: 99%

Bayesian Synthetic Control Methods

Kim¹,

Lee²,

Gupta³

2020

Journal of Marketing Research

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The authors propose a new Bayesian synthetic control framework to overcome limitations of extant synthetic control methods (SCMs). The proposed Bayesian synthetic control methods (BSCMs) do not impose any restrictive constraints on the parameter space a priori. Moreover, they provide statistical inference in a straightforward manner as well as a natural mechanism to deal with the “large p, small n” and sparsity problems through Markov chain Monte Carlo procedures. Using simulations, the authors find that for a variety of data-generating processes, the proposed BSCMs almost always provide better predictive accuracy and parameter precision than extant SCMs. They demonstrate an application of the proposed BSCMs to a real-world context of a tax imposed on soda sales in Washington state in 2010. As in the simulations, the proposed models outperform extant models, as measured by predictive accuracy in the posttreatment periods. The authors find that the tax led to an increase of 5.7% in retail price and a decrease of 5.5%∼5.8% in sales. They also find that retailers in Washington overshifted the tax to consumers, leading to a pass-through rate of approximately 121%.

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ArCo: An R package to Estimate Artificial Counterfactuals

Cited by 5 publications

References 15 publications

The effect of interest rate caps on bankruptcy: Synthetic control evidence from recent payday lending bans

The effect of interest rate caps on bankruptcy: Synthetic control evidence from recent payday lending bans

The Effect of the Great Recession on Italian Life Expectancy

Bayesian Synthetic Control Methods

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