Macroeconomic effects of a decade-long EU membership: evidence from Croatia

The synthetic control method (Abadie and Gardeazabal, 2003, American Economic Review 93: 113–132, Abadie, Diamond, and Hainmueller, 2010, Journal of the American Statistical Association 105: 493–505) is a popular method for causal inference in panel data with one treated unit that often uses placebo tests for statistical inference. While the synthetic control method can be implemented by the excellent command synth (Abadie, Diamond, and Hainmueller, 2011, Statistical Software Components S457334, Department of Economics, Boston College), it is still inconvenient for users to conduct placebo tests. As a wrapper program for synth, our proposed synth2 command provides convenient utilities to automate both in-space and in-time placebo tests, as well as the leave-one-out robustness test. Moreover, synth2 produces a complete set of graphs to visualize covariate or unit weights, covariate balance, actual or predicted outcomes, treatment effects, placebo tests, ratio of posttreatment mean squared prediction error to pretreatment mean squared prediction error, pointwise p-values (two-sided, right-sided, and left-sided), and the leave-one-out robustness test. We illustrate the use of the synth2 command by revisiting the classic example of California’s tobacco control program (Abadie, Diamond, and Hainmueller 2010).

This study empirically assesses the growth effect of adopting the euro by applying a recently developed econometric technique, the synthetic control method (SCM), to implement data-driven comparative case studies for the euro zone. For analytical purposes, we classify the 12 euro-adopting countries into two country groups: core and peripheral countries. The results from the SCM algorithm show that the patterns of per capita GDP in the core (peripheral) countries are generally lower (higher) than those of their counterfactual units. However, the outcomes of the placebo tests indicate that these differences are statistically insignificant, thus implying that the introduction of the euro system neither improves nor impairs the economic growth of these two groups of countries that adopted the euro during 1991-2013. As for the three European Union countries that did not adopt the euro, the results of the inverse SCM analysis show that Denmark would be better off if it had adopted the euro. However, in the cases of Sweden and the United Kingdom, not adopting the euro system may have been a better choice, especially following the sovereign debt crisis.

IntroductionThis paper discusses the application of the synthetic control method to injury-related interventions using aggregate data from public information systems. The method selects and determines the optimal control unit in...

Background Wolbachia symbiosis in Aedes aegypti is an emerging biocontrol measure against dengue. However, assessing its real-world efficacy is challenging due to the non-randomised, field-based nature of most intervention studies. This research re-evaluates the spatial-temporal impact of Wolbachia interventions on dengue incidence using a large battery of quasi-experimental methods and assesses each method’s validity. Aggregated intervention efficacies by event time for each study site Aggregated intervention efficacies for (a) Selangor, (b) Niterói, and (c) Singapore based on event time. Each efficacy assessment method is represented by a specific color: red for Pre-post, yellow for RDD (Regression Discontinuity Design), green for 2x2 DiD (Difference-in-Differences), blue for SCM (Synthetic Control Method), and purple for cSCM (count Synthetic Control Method). The intervention efficacy (IE) reported in the original paper is depicted on the right side of each diagram, represented by the colour black. The dot represents the IE point estimate for each method, while the line indicates the corresponding confidence intervals. Extreme confidence interval values and point estimates are denoted by arrows, with their respective values displayed next to the arrow. Methods A systematic search for Wolbachia intervention data was conducted via PUBMED. Efficacy was reassessed using commonly-used quasi-experimental approaches with extensive robustness checks, including geospatial placebo tests and a simulation study. Intervention efficacies across multiple study sites were computed using high-resolution aggregations to examine heterogeneities across sites and study periods. We further designed a stochastic simulation framework to assess the methods’ ability to estimate intervention efficacies (IE). Aggregate intervention efficacy (IE) estimates (%) of Wolbachia releases on total dengue incidence rates across all intervention sitesTable 2:Aggregate intervention efficacy (IE) estimates (%) of Wolbachia releases on total dengue incidence rates across all intervention sites. The estimates are reported for each method and are accompanied by the corresponding confidence intervals (in parentheses). The IE estimate reported in the respective original papers, highlighted in blue, is provided for comparison. Numbers in parenthesis represent lower and upper bounds for 95% confidence intervals, estimated using the bootstrapping procedure. # indicates that the estimate passed in-time placebo checks while * indicates that it passed in-space placebo check. Bolded figures represent significant IE estimates which also passed in-space and in-time placebo checks. Results Wolbachia interventions in Singapore, Malaysia, and Brazil significantly decreased dengue incidence, with reductions ranging from 48.17% to 69.19%. IEs varied with location and duration. Selangor showed increasing efficacy over time, while Niterói exhibited initial success with subsequent decline, hinting at operational challenges. Singapore's strategy was highly effective despite partial saturation. Simulations identified Synthetic Control Methods (SCM) and its variant, count Synthetic Control Method (cSCM), as superior in precision, with the smallest percentage errors in efficacy estimation. These methods also demonstrated robustness in placebo tests. Conclusion Wolbachia interventions exhibit consistent protective effects against dengue. SCM and cSCM provided the most precise and robust estimates of IEs, validated across simulated and real-world settings. Disclosures All Authors: No reported disclosures

Estimating treatment (or policy or intervention) effects on a single individual or unit has become increasingly important in health and biomedical sciences. One method to estimate these effects is the synthetic control method, which constructs a synthetic control, a weighted average of control units that best matches the treated unit's pre-treatment outcomes and other relevant covariates. The intervention's impact is then estimated by comparing the post-intervention outcomes of the treated unit and its synthetic control, which serves as a proxy for the counterfactual outcome had the treated unit not experienced the intervention. The augmented synthetic control method, a recent adaptation of the synthetic control method, relaxes some of the synthetic control method's assumptions for broader applicability. While synthetic controls have been used in a variety of fields, their use in public health and biomedical research is more recent, and newer methods such as the augmented synthetic control method are underutilized. This paper briefly describes the synthetic control method and its application, explains the augmented synthetic control method and its differences from the synthetic control method, and estimates the effects of an antimalarial initiative in Mozambique using both the synthetic control method and the augmented synthetic control method to highlight the advantages of using the augmented synthetic control method to analyze the impact of interventions implemented in a single region.

BackgroundThe synthetic control method (SCM) is a useful tool in providing unbiased analysis on the policy effect in real-world health policy evaluations. Through controlling for a few confounding factors, we aim to apply SCM in analyzing the impact of the pricing reform on medical expenditure structure in Jiangsu Province, China.MethodsWe constructed a synthetic control for Zhenjiang, a city where the reform was piloted in Jiangsu, by selecting weights on those potential control units to define a linear combination of the control outcomes to replicate the counterfactual as if the intervention is in absence. The policy effect was measured by the differences in the percentage of drug expenditure among average outpatient and inpatient care cost per visit in the post-policy period between Zhenjiang and its synthetic control. We also examined the significance of the estimated results by performing placebo tests, and cross-validated the results with a difference-in-differences analysis.ResultsThe medical pricing reform was found to be effective in reducing the drug expenditure proportions in both outpatient and inpatient care by an estimated mean level of 7.7 and 3.2% (or 16.3 and 9.2% relative decrease to their 2012 levels) respectively. This reform effect was estimated to be significant in the placebo tests and was further confirmed by a cross-validation.ConclusionWe conclude that the pricing reform in public hospitals has significantly reduced drug expenditure incurred in both outpatient and inpatient care. This study also highlights the applicability of SCM method as an effective tool for health policy evaluation using publicly available data in the context of Chinese healthcare system.

In order to develop green finance and realize the coordinated development of the environment and economy, China established green finance reform and innovation pilot zones in 2017. Green innovation has problems such as low financing utilization rate and lack of market competitiveness. The green finance pilot policies (GFPP) based on government management provide solutions to these problems. It is of great significance to measure and provide feedback on the implementation effect of GFPP in China for policy-making and green development. This article focuses on the influence of the construction of GFPP by using the five pilot zones as the study area and constructs the green innovation level indicator. Based on the synthetic control method, it chooses provinces that do not carry out the pilot policy as a control group. After that, assign weights to the control region to fit a synthetic control group with resembling characteristics to simulate the five pilot provinces without implementing the policy. Then, compare it with its current policy effect and highlight the policy implementation effect on green innovation. The placebo test and robustness test were conducted to prove the reliability of the conclusions. The results show that since the implementation of GFPP, the level of green innovation in the five pilot cities has shown an overall rising trend. Furthermore, we found that the balance of credit and investment in science and technology has a negative moderating effect on the implementation of GFPP, while the per capita GDP has a significant positive moderating effect.

To launch the nationwide emission trading scheme, some provinces in China were approved to design their pilot work for emission trading scheme according to local circumstances. Shanxi Province is the only pilot area with provincial trading market for industrial soot and dust emissions. This paper investigates the effect of Shanxi Pilot emission trading scheme on industrial soot and dust emissions by using the synthetic control method. The idea behind the synthetic control approach is to construct a combination of comparison cities to approximate the emission paths that the cities in Shanxi would have experienced in the absence of the pilot emission trading scheme. We demonstrate that, following Shanxi Pilot emission trading scheme, industrial soot and dust emissions fell markedly in Taiyuan, Datong, and Linfen relative to the synthetic counterparts. The finding that emission trading scheme can help achieve emission reduction targets is shown to be robust to the reduction in the number of control units, placebo tests, and difference-in-differences estimation.

Despite growing concern about the low-carbon economic development, little is known about the role of political institutions, democracy, or the absence thereof, in controlling carbon intensity (carbon dioxide emissions per unit of GDP). This paper estimates the causal effects of democratic transition in Indonesia on its national carbon emission intensity. The synthetic control method is adopted to handle both time-invariant and time-variant confounding heterogeneity. Results show that Indonesia's democratic transition increases on average 0.24kg carbon dioxide emissions per constant 2005 US dollar in the post-transition period (1999-2010), a rise of approximately 25.34%. The placebo tests indicate this causal effect is significant and the leave-one-out sensitivity check also demonstrates its robustness. The evidence of Indonesia suggests that democratic transition may serve to intensify, rather than mitigate, the emissions of carbon dioxide. Therefore, policymakers should pay more attentions to the contextual fit of democratic transition.

Causal inference from observational data remains a significant challenge for scholars and policymakers, particularly in assessing the impact of public health policies where randomization is often infeasible. To evaluate the impact of the Yellow September campaign on suicide rates in Brazil using the synthetic control method (SCM). A quasi-experimental design was applied using annual suicide rate data from 2000 to 2019. Socioeconomic and demographic variables were obtained from the World Bank and WHO datasets. The SCM was employed to construct a counterfactual scenario simulating suicide rates in the absence of the campaign, using Latin American countries as control units. The synthetic control model demonstrated a strong alignment between Brazil and its synthetic counterpart in the pre-intervention period. However, post-2015 analysis revealed a 9.2% increase in suicide rates in Brazil compared to the synthetic control. Brazil exhibited a post-/pre-intervention RMSPE ratio of 4.18, the highest among all countries in the donor pool. However, placebo tests indicated that this observed increase was not statistically significant, suggesting the difference may reflect random variation or other factors unrelated to the campaign. The Yellow September campaign had no statistically significant impact on reducing suicide rates in Brazil. While the observed increase in suicide rates may reflect improved case reporting or contextual influences, these findings underscore the complexity of evaluating mental health policies. Complementary strategies and further research are needed to better understand the campaign's effects and address the multifaceted nature of suicide prevention.

<h3>Statement of Purpose</h3> Firearm suicide is a leading cause of death for nearly every age group 10–14 years and older in the U.S. In 2019, a firearm was used in half of all suicides. Despite research demonstrating that impulsive suicide attempts are far from uncommon, few studies have examined the effectiveness of firearm purchase waiting periods as a tool to restrict access to lethal means and prevent suicide. The present study estimates the effect of a waiting period repeal on handgun suicide rates. <h3>Methods/Approach</h3> I use a quasi-experimental design and the synthetic control method to estimate the effect of Wisconsin’s handgun purchase waiting period repeal on the handgun suicide rate. Annual state-level suicide and sociodemographic data from 1999–2019 were included. Placebo tests and difference-in-difference regression were used to supplement results from the synthetic control analysis. <h3>Results</h3> The proportion of suicides involving handguns increased from 25.3% to 32.4% following the repeal; post-intervention suicides were more likely to involve handguns than those in the pre-intervention period [χ² (1, N = 8269) = 49.25, p &lt; .001]. A ‘synthetic Wisconsin’ closely approximated the pre-intervention handgun suicide rate in Wisconsin (mean squared prediction error = 0.04). The estimated treatment effect of the waiting period repeal is 1.16 deaths per 100,000, which translates to a 31% increase in the handgun suicide rate. Estimates from the difference-in-difference regressions indicated a similar treatment effect. <h3>Conclusions</h3> Allowing for the immediate acquisition of a handgun at the point-of-sale in Wisconsin resulted in an estimated mean annual increase of 67 handgun suicides. <h3>Significance</h3> The findings add to the limited research on firearm purchase waiting periods by using a data-driven method to estimate the causal effect of repeal. The synthetic control’s ability to closely approximate pre-intervention trends despite a limited donor pool of control states has implications for future policy analyses.

BACKGROUND:Critics of free trade agreements have argued that they threaten public health, as they eliminate barriers to trade in potentially harmful products, such as sugar. Here we analyze the North American Free Trade Agreement (NAFTA), testing the hypothesis that lowering tariffs on food and beverage syrups that contain high-fructose corn syrup (HFCS) increased its use in foods consumed in Canada.METHODS:We used supply data from the Food and Agriculture Organization of the United Nations to assess changes in supply of caloric sweeteners including HFCS after NAFTA. We estimate the impact of NAFTA on supply of HFCS in Canada using an innovative, quasi-experimental methodology — synthetic control methods — that creates a control group with which to compare Canada’s outcomes. Additional robustness tests were performed for sample, control groups and model specification.RESULTS:Tariff reductions in NAFTA coincided with a 41.6 (95% confidence interval 25.1 to 58.2) kilocalorie per capita daily increase in the supply of caloric sweeteners including HFCS. This change was not observed in the control groups, including Australia and the United Kingdom, as well as a composite control of 16 countries. Results were robust to placebo tests and additional sensitivity analyses.INTERPRETATION:NAFTA was strongly associated with a marked rise in HFCS supply and likely consumption in Canada. Our study provides evidence that even a seemingly modest change to product tariffs in free trade agreements can substantially alter population-wide dietary behaviour and exposure to risk factors.

Does China’s carbon emission trading scheme reduce CO[formula omitted] emissions? Comprehensive evaluation from synthetic control method using lasso

The effectiveness of pharmaceutical tenders as a cost containment mechanism: analysis through the Synthetic Control Method. The case of Andalusia (Spain).

The economic effects of a counterinsurgency policy in India: A synthetic control analysis