Synthetic Control Research Articles

The effect of EU membership on tourism in Croatia

This study examines the impact of EU membership on tourism in Croatia, one of the most important economic sectors in the country. Using the counterfactual synthetic control method, the causal effect of EU membership on overnight tourists in Croatia in the period from 2013 to 2021 is estimated. The results suggest there is a large, positive, and long-term effect of the EU joining on overnight visitors in Croatia, with European tourists being the main contributors to tourism growth. In the period before COVID-19, the maximum discrepancy between the observed number of tourists and the synthetic value was achieved in 2017, with Croatia receiving an additional 3 million visitors, or 23 percent more than the value of the synthetic. Although these results are context-specific, the resemblance of Croatia to some EU candidate countries provides insights into possible tourism outcomes of integration in Europe.

Estimating treatment effect in randomized trial after control to treatment crossover using external controls

ABSTRACT In clinical trials, it is common to design a study that permits the administration of an experimental treatment to participants in the placebo or standard of care group post primary endpoint. This is often seen in the open-label extension phase of a phase III, pivotal study of the new medicine, where the focus is on assessing long-term safety and efficacy. With the availability of external controls, proper estimation and inference of long-term treatment effect during the open-label extension phase in the absence of placebo-controlled patients are now feasible. Within the framework of causal inference, we propose several difference-in-differences (DID) type methods and a synthetic control method (SCM) for the combination of randomized controlled trials and external controls. Our realistic simulation studies demonstrate the desirable performance of the proposed estimators in a variety of practical scenarios. In particular, DID methods outperform SCM and are the recommended methods of choice. An empirical application of the methods is demonstrated through a phase III clinical trial in rare disease.

Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets: a synthetic-control approach

Abstract In cities, the creation of public transport infrastructure such as light rails can cause changes on a very detailed spatial scale, with different stories unfolding next to each other within the same urban neighbourhood. We study the direct effect of a light rail line built in Florence (Italy) on the retail density of the street where it was built and its spillover effect on other streets in the treated street’s neighbourhood. To this aim, we investigate the use of the synthetic control group (SCG) methods in panel comparative case studies where interference between the treated and the untreated units is plausible, an issue still little researched in the SCG methodological literature. We frame our discussion in the potential outcomes approach. Under a partial interference assumption, we formally define relevant direct and spillover causal effects.

Estimating the return on investment of the New York Tobacco Control Programme: a synthetic control study

ObjectiveTo assess the return on investment (ROI) of the New York Tobacco Control Programme (NY TCP).SettingNew York and other states of the USA.InterventionsNY TCP.OutcomesSmoking prevalence, smoking-attributable healthcare expenditures (SAEs), smoking-attributable...

Oil boom, rent sharing, job prospects and human capital investment: Evidence from Chad

A large body of literature shows that the drop in educational attainment resulting from the resource boom is one of the major drivers of the so-called resource curse. This paper explores how upstream actions can avoid this resource curse and promote human capital development at the local level. Specifically, I examine how a rent-sharing model and the employment opportunities induced by an oil boom for native populations affect secondary education decisions in Chad’s oil region. Using a synthetic control method, I find that these measures increased secondary school attendance in the region. Similar results were obtained using a difference-in-differences approach. In terms of mechanisms, the results show that labor market opportunities and regulations were more effective in promoting investment in education than the rent-sharing model. Finally, I note that these measures reduced dropouts rather than increasing attendance at all levels.

Synthetic control over the energy transfer and charge transfer between carbon dots and covalent organic framework

Carbon dots (CDs) are environmentally benign, strongly photoluminescent, metal free nanoparticles. Interfacing them with tailor-made organic semiconductors possesing an ordered channel structure such as covalent organic frameworks (COFs) promises to yield multifunctional materials. In this study, microwave-derived CDs are successfully incorporated into the porous structure of COF in a one-pot synthesis in which the condensation reaction between benzo[1,2-b:4,5-b′]dithiophene-2,6-dicarboxaldehyde (BDT) and 1,1,2,2-tetra(p-aminophenyl)ethylene (ETTA) is conducted in the presence of CDs. A detailed structural and optoelectronic characterization of the COF/CDs composite reveals that upon tuning the CDs loadings encapsulated in COF the interaction between both components can be controlled allowing the switch between energy and charge transfer. At CDs loadings ⩽20 wt%, strong binding of CDs to the COF enables charge transfer evinced from the quenched photoluminescence (PL) of both components and accelerated exciton decay kinetics of the COF. At CDs loadings ⩾30 wt% Förster resonance energy transfer from CDs to COF prevails, leading to enhanced COF PL. Our study underlines the interaction mechanism in organic composites and provides the knowledge required for the design of novel functional materials with applications in photocatalysis, optoelectronics and sensing.

Direct potable reuse and birth defects prevalence in Texas: An augmented synthetic control method analysis of data from a population-based birth defects registry.

Direct potable reuse (DPR) involves adding purified wastewater that has not passed through an environmental buffer into a water distribution system. DPR may help address water shortages and is approved or is under consideration as a source of drinking water for several water-stressed population centers in the United States, however, there are no studies of health outcomes in populations who receive DPR drinking water. Our objective was to determine whether the introduction of DPR for certain public water systems in Texas was associated with changes in birth defect prevalence. We obtained data on maternal characteristics for all live births and birth defects cases regardless of pregnancy outcome in Texas from 2003 to 2017 from the Texas Birth Defects Registry and birth and fetal death records. The ridge augmented synthetic control method was used to model changes in birth defect prevalence (per 10,000 live births) following the adoption of DPR by four Texas counties in mid-2013, with county-level data on maternal age, percent women without a high school diploma, percent who identified as Hispanic/Latina or non-Hispanic/Latina Black, and rural-urban continuum code as covariates. There were nonstatistically significant increases in prevalence of all birth defects collectively (average treatment effect in the treated = 53.6) and congenital heart disease (average treatment effect in the treated = 287.3) since June 2013. The estimated prevalence of neural tube defects was unchanged. We estimated nonstatistically significant increases in birth defect prevalence following the implementation of DPR in four West Texas counties. Further research is warranted to inform water policy decisions.

Acaricide Potential of Creosote Bush (Larrea tridentata) Extracts in the Control of Varroa destructor in Apis mellifera

The aim of the present study was to assess the potential of natural compounds for the control of Varroa destructor in colonies of Apis mellifera, the antimite potential of the hydrolate and ethanolic extract (Leatricina®) of creosote bush (Larrea tridentata) was evaluated at a concentration 50%; contrasting them with the synthetic chemical amitraz and control under in vitro conditions (48 h) and in the hive (52 days). There were differences (p<0.05) in In vitro Varroa mortality with amitraz with higher values (97.9%) compared with hydrolate (53.1%) and Leatricina® (51.5%); Creosote bush extracts were similar (p> 0.05). In the field experiment, the reduction in the percentage of varroa infestation in adult bees was higher 84.9 % (p<0.05) for amitraz, while the hydrolate and Leatricina® showed differences (p<0.05) 49.5 and 72% respectively, the control group showed the lowest values. Even when the effectiveness of synthetic chemicals presents an evident superiority, the average efficacy and other benefits of natural compounds such as creosote bush extracts represent a viable and safe alternative for the control of V. destructor.

Policy legacies and energy transitions: Greening policies under sectoral reforms in Argentina and Chile

Under what conditions do greening policies lead to a fast deployment of solar and wind energies? Environmental economics assume that market factors and technological innovations are the main drivers of energy transitions. While these assumptions sometimes hold for well-functioning markets; in emerging economies, the combination of scarce capital, weak institutions, and market distortions creates specific challenges that make their paths to clean energies different from those of developed states. I analyze greening reforms of the electricity sector in Argentina and Chile, exploring instances of success and failure. Using archive data and interviews to stakeholders, I explain how previous sector structures created different market distortions that hindered an effective electricity transition even in the context of significant cost-savings from investment in new technologies. Successful greening policies entailed broader electricity-sector reforms that removed previous binding constraints and restructured incentives for key private-sector stakeholders. I corroborate this argument by employing synthetic control methods to evaluate policies’ impact. I show that broad greening policies led to a significant penetration of renewable energies: by 2020 the share of solar and wind energies in Argentina and Chile were about 7.3% and 13.6% higher than in the counterfactual scenarios in which the greening reforms had not occurred.

The impact of devolution on local health systems: Evidence from Greater Manchester, England

Devolution and decentralisation policies involving health and other government sectors have been promoted with a view to improve efficiency and equity in local service provision. Evaluations of these reforms have focused on specific health or care measures, but little is known about their full impact on local health systems. We evaluated the impact of devolution in Greater Manchester (England) on multiple outcomes using a whole system approach.We estimated the impact of devolution until February 2020 on 98 measures of health system performance, using the generalised synthetic control method and adjusting for multiple hypothesis testing. We selected measures from existing monitoring frameworks to populate the WHO Health System Performance Assessment framework. The included measures captured information on health system functions, intermediatory objectives, final goals, and social determinants of health. We identified which indicators were targeted in response to devolution from an analysis of 170 health policy intervention documents.Life expectancy (0.233 years, S.E. 0.012) and healthy life expectancy (0.603 years, S.E. 0.391) increased more in GM than in the estimated synthetic control group following devolution. These increases were driven by improvements in public health, primary care, hospital, and adult social care services as well as factors associated with social determinants of health, including a reduction in alcohol-related admissions (−110.1 admission per 100,000, S.E. 9.07). In contrast, the impact on outpatient, mental health, maternity, and dental services was mixed.Devolution was associated with improved population health, driven by improvements in health services and wider social determinants of health. These changes occurred despite limited devolved powers over health service resources suggesting that other mechanisms played an important role, including the allocation of sustainability and transformation funding and the alignment of decision-making across health, social care, and wider public services in the region.

Staggered deployment of gunshot detection technology in Chicago, IL: a matched quasi-experiment of gun violence outcomes

Abstract Objectives We examine the potential effects of gunshot detection technology longitudinally in Chicago through a synthetic control quasi-experiment. Methods Police districts receiving gunshot detection technology were compared to a synthetic control unit via a staggered difference-in-difference design. Across eleven unique gunshot detection technology deployment phases, the analyses produce results for aggregate, initial versus expanded, and phase-specific deployment effects across five gun violence outcome measures. Results Gunshot detection technology had no effect on fatal shootings, non-fatal shootings, general part I gun crimes, or shots fired calls for service. Gun recoveries significantly increased in the aggregate, initial, and expanded models, and in several individual phases relative to controls. Conclusions The results align with prior literature that has found a procedural benefit, but not a crime prevention benefit, of gunshot detection technology. Law enforcement agencies seeking crime prevention or reduction solutions may be better served by investing in other options.

The effects of membership expansion on credit union risk and returns

Between 1996 and 2022, regulatory changes led to over a thousand federally chartered credit unions converting to community charters, significantly increasing credit union membership. This study attempts to determine whether these developments improve safety and soundness by enabling credit unions to diversify their loan portfolios, or whether risk increases as the social capital of a tight common bond becomes diluted. We use two-way fixed effects, doubly robust and generalized synthetic control methods with state chartered credit unions and commercial banks as controls to estimate both intent-to-treat (ITT) and average treatment-effect-on-the-treated (ATT) impacts on credit union risk and returns. We find that conversions to community charter unambiguously improve credit union returns but the effects on risk are mixed: liquidity and capital fall, but there is no change in indicators of asset quality. Overall, during the 25-year period from 1998 to 2022, only 1.47% of community-chartered credit unions failed. The results suggest that social capital is no longer an important factor in reducing credit risk in countries with developed financial sectors like the U.S.

Engineered algal systems for the treatment of anaerobic digestate: A meta-analysis

The objective of this review was to provide quantitative insights into algal growth and nutrient removal in anaerobic digestate. To synthesize the relevant literature, a meta-analysis was conducted using data from 58 articles to elucidate key factors that impact algal biomass productivity and nutrient removal from anaerobic digestate. On average, algal biomass productivity in anaerobic digestate was significantly lower than that in synthetic control media (p < 0.05) but large variation in productivity was observed. A mixed-effects multiple regression model across study revealed that biological or chemical pretreatment of digestate significantly increase productivity (p < 0.001). In contrast, the commonly used practice of digestate dilution was not a significant factor in the model. High initial total ammonia nitrogen suppressed algal growth (p = 0.036) whereas initial total phosphorus concentration, digestate sterilization, CO2 supplementation, and temperature were not statistically significant factors. Higher growth corresponded with significantly higher NH4–N and phosphorus removal with a linear relationship of 6.4 mg NH4–N and 0.73 mg P removed per 100 mg of algal biomass growth (p < 0.001). The literature suggests that suboptimal algal growth in anaerobic digestate could be due to factors such as turbidity, high free ammonia, and residual organic compounds. This analysis shows that non-dilution approaches, such as biological or chemical pretreatment, for alleviating algal inhibition are recommended for algal digestate treatment systems.

Abstract 3618: High-avidity BCMA CAR and high-affinity, non-cleavable CD16 Fc receptor incorporated in off-the-shelf CAR T cells promote multi-antigen targeting and durable anti-tumor cytotoxicity in the treatment of multiple myeloma

Abstract Immune cell therapy has proven highly effective for the treatment of multiple myeloma (MM). However, key challenges remain that include disease relapse, limited patient access, and inability to effectively combine with existing standard-of-care therapies. Rapid progress in the development of off-the-shelf, multiplexed-engineered, induced pluripotent stem cell (iPSC)-derived cell therapies enables large-scale manufacture of immune cells incorporating multiple novel synthetic controls of cell function to improve cell fitness, enhance cell function, and enable synergistic combination with existing effective therapies such as CD38-targeted antibody (mAb) therapy. We have developed an iPSC-derived chimeric antigen receptor T (CAR-iT) cell therapy that uniquely leverages elements of both adaptive and innate immunity by incorporating a BCMA-targeted CAR (BCMA-CAR) derived from a scFv domain exhibiting high-binding affinity in the low nanomolar range, and a high-affinity, non-cleavable CD16 (hnCD16) Fc receptor to enable antibody-dependent cellular cytotoxicity with mAb therapy. The genetic deletion of CD38 gene was also incorporated to eliminate the possibility for CD38-mediated fratricide, and genetic deletion of TRAC gene was introduced to remove the potential risk of graft-versus-host disease in an allogeneic setting. These CAR iT cells, which were generated from a clonally-derived iPSC line, demonstrated homogenous expression of each genetic edit (&amp;gt;95% BCMA-CAR and hnCD16; &amp;lt;1% CD38 and TCR surface expression). Using a stringent, disseminated xenograft mouse model of multiple myeloma, MM.1S, which was allowed to achieve complete systemic engraftment during the initial 4 days, treatment with BCMA-CAR iT cells demonstrated comparable tumor cell clearance (p=0.0024 vs. vehicle at Day 17) to primary BCMA-CAR T cells (p=0.002 vs. vehicle). In combination with a CD38-targeted mAb to exploit hnCD16 and biallelic CD38 KO, BCMA-CAR iT cells are capable of dual-antigen targeting to address antigen escape and promote durable tumor control. To this end, a single dose of BCMA-CAR iT cells combined with daratumumab exhibited near complete TGI for the duration of the study (p&amp;lt;0.0001 vs. vehicle at Day 37). Together, these studies demonstrate CAR iT cells incorporating a high-avidity BCMA CAR and high-affinity, non-cleavable CD16 Fc receptor can uniquely leverage elements of both adaptive and innate immunity and can be combined with CD38-targeted mAb to potentially outcompete primary BCMA CAR T cells. As these CAR iT cells can be administered off-the-shelf, key challenges associated with current immune cell therapy, such as patient access and inability to synergize with standard-of-care therapies, can be addressed for the treatment of relapsed/refractory MM. Citation Format: John Reiser, Alison O'Connor, Bryan Hancock, Spas Markov, Brian Groff, Alma Gutierrez, Miguel Meza, Mark Jelcik, Yijia Pan, Alex Garcia, Bobby Goulding, Matthew Denholtz, Tom Lee, Ramzey Abujarour, Ryan Bjordahl, Armin Rehm, Raedun Clarke, Jode Goodridge, Bahram Valamehr. High-avidity BCMA CAR and high-affinity, non-cleavable CD16 Fc receptor incorporated in off-the-shelf CAR T cells promote multi-antigen targeting and durable anti-tumor cytotoxicity in the treatment of multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3618.

From the French franc to the euro, is there an economic impact for the CFA franc zone countries? A ‘bias-corrected’ synthetic control method

From the French franc to the euro, is there an economic impact for the CFA franc zone countries? A ‘bias-corrected’ synthetic control method

Comparing the Efficacy of Two Generations of EGFR-TKIs: An Integrated Drug-Disease Mechanistic Model Approach in EGFR-Mutated Lung Adenocarcinoma.

Mutationsin epidermal growth factor receptor (EGFR) are found in approximately 48% of Asian and 19% of Western patients with lung adenocarcinoma (LUAD), leading to aggressive tumor growth. While tyrosine kinase inhibitors (TKIs) like gefitinib and osimertinib target this mutation, treatments often face challenges such as metastasis and resistance. To address this, we developed physiologically based pharmacokinetic (PBPK) models for both drugs, simulating their distribution within the primary tumor and metastases following oral administration. These models, combined with a mechanistic knowledge-based disease model of EGFR-mutated LUAD, allow us to predict the tumor's behavior under treatment considering the diversity within the tumor cells due to different mutations. The combined model reproduces the drugs' distribution within the body, as well as the effects of both gefitinib and osimertinib on EGFR-activation-induced signaling pathways. In addition, the disease model encapsulates the heterogeneity within the tumor through the representation of various subclones. Each subclone is characterized by unique mutation profiles, allowing the model to accurately reproduce clinical outcomes, including patients' progression, aligning with RECIST criteria guidelines (version 1.1). Datasets used for calibration came from NEJ002 and FLAURA clinical trials. The quality of the fit was ensured with rigorous visual predictive checks and statistical tests (comparison metrics computed from bootstrapped, weighted log-rank tests: 98.4% (NEJ002) and 99.9% (FLAURA) similarity). In addition, the model was able to predict outcomes from an independent retrospective study comparing gefitinib and osimertinib which had not been used within the model development phase. This output validation underscores mechanistic models' potential in guiding future clinical trials by comparing treatment efficacies and identifying patients who would benefit most from specific TKIs. Our work is a step towards the design of a powerful tool enhancing personalized treatment in LUAD. It could support treatment strategy evaluations and potentially reduce trial sizes, promising more efficient and targeted therapeutic approaches. Following its consecutive prospective validations with the FLAURA2 and MARIPOSA trials (validation metrics computed from bootstrapped, weighted log-rank tests: 94.0% and 98.1%, respectively), the model could be used to generate a synthetic control arm.

The effect of cap-and-trade on sectoral emissions: Evidence from California

We study the impact of California’s cap-and-trade system on carbon emissions in the electricity and industrial sectors. We use US state-level panel data covering the period 2005–2019 and apply the synthetic control method to construct an optimal counterfactual for per capita emissions in each sector. In our experiment, emissions in the power sector fall below counterfactual emissions by 48%. In the industrial sector, the state’s emissions are 6% higher than those of the synthetic control unit by the end of the observation period. Thus, cap-and-trade failed to deliver decarbonization across both sectors. While the abatement in the power sector was facilitated by complementary policies and driven by a switch from natural gas to renewables, California’s policy mix has disincentivized emission reductions in the industrial sector.

A universal molecular control for DNA, mRNA and protein expression

The expression of genes encompasses their transcription into mRNA followed by translation into protein. In recent years, next-generation sequencing and mass spectrometry methods have profiled DNA, RNA and protein abundance in cells. However, there are currently no reference standards that are compatible across these genomic, transcriptomic and proteomic methods, and provide an integrated measure of gene expression. Here, we use synthetic biology principles to engineer a multi-omics control, termed pREF, that can act as a universal molecular standard for next-generation sequencing and mass spectrometry methods. The pREF sequence encodes 21 synthetic genes that can be in vitro transcribed into spike-in mRNA controls, and in vitro translated to generate matched protein controls. The synthetic genes provide qualitative controls that can measure sensitivity and quantitative accuracy of DNA, RNA and peptide detection. We demonstrate the use of pREF in metagenome DNA sequencing and RNA sequencing experiments and evaluate the quantification of proteins using mass spectrometry. Unlike previous spike-in controls, pREF can be independently propagated and the synthetic mRNA and protein controls can be sustainably prepared by recipient laboratories using common molecular biology techniques. Together, this provides a universal synthetic standard able to integrate genomic, transcriptomic and proteomic methods.

Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence

Clinical research relies on high-quality patient data, however, obtaining big data sets is costly and access to existing data is often hindered by privacy and regulatory concerns. Synthetic data generation holds the promise of effectively bypassing these boundaries allowing for simplified data accessibility and the prospect of synthetic control cohorts. We employed two different methodologies of generative artificial intelligence – CTAB-GAN+ and normalizing flows (NFlow) – to synthesize patient data derived from 1606 patients with acute myeloid leukemia, a heterogeneous hematological malignancy, that were treated within four multicenter clinical trials. Both generative models accurately captured distributions of demographic, laboratory, molecular and cytogenetic variables, as well as patient outcomes yielding high performance scores regarding fidelity and usability of both synthetic cohorts (n = 1606 each). Survival analysis demonstrated close resemblance of survival curves between original and synthetic cohorts. Inter-variable relationships were preserved in univariable outcome analysis enabling explorative analysis in our synthetic data. Additionally, training sample privacy is safeguarded mitigating possible patient re-identification, which we quantified using Hamming distances. We provide not only a proof-of-concept for synthetic data generation in multimodal clinical data for rare diseases, but also full public access to synthetic data sets to foster further research.

Unleashing digital empowerment: Pioneering low-carbon development through the broadband China strategy

Low-carbon development has emerged as an imperative in the pursuit of carbon peak and neutrality. To this end, the intersection of digital empowerment and the quest for innovative solutions in developing countries has taken center stage, particularly in exploring the network infrastructure construction potential. This research delves into the intricate relationship between network infrastructure construction expansion and low-carbon development in developing countries, drawing insights from a comprehensive analysis of panel data collected from 282 Chinese cities. Leveraging the quasi-natural experiment presented by “Broadband China” and employing a rigorous multi-period difference-in-difference (DID) model, our study uncovers significant findings. First, it reveals that the expansion of the network infrastructure construction directly amplifies the prospects of low-carbon development, a result consistently upheld through meticulous assessments of the multi-period DID approach and validation through the robust synthetic control DID method. Second, the study elucidates how network infrastructure construction expansion fosters low-carbon development by optimizing industrial structure and promoting investments in cutting-edge technologies. Third, it unveils the impact of network infrastructure construction expansion on the efficiency of low-carbon technology, concurrently encouraging its enhancement while imposing specific inhibitory effects. Remarkably, the policy outcomes exhibit variations among cities of differing sizes and between cities with old and non-old industrial bases. Finally, the research underscores the spatially endogenous interaction effects within low-carbon development. In sum, this study not only enriches comprehension of innovative avenues for low-carbon development within the sphere of digital empowerment but also provides empirical evidence to refine policy recommendations specifically tailored to the unique context of developing countries.