Synthetic Control Research Articles

Policy evaluation and optimization for photovoltaic poverty alleviation projects in Anhui Province of China

To synergize climate mitigation with poverty alleviation, China has implemented photovoltaic poverty alleviation (PVPA) projects since 2014, with Anhui Province being among the initial pilot regions. However, further exploration is needed to determine the extent to which this policy can improve the economic status of poverty-stricken areas. This study aims to evaluate the effects of PVPA projects in Anhui Province from a macroscopic perspective and via the panel data from 11 poverty-stricken counties, including 5 pilot counties, between 2011 and 2018. By employing the differences-in-differences (DID) model and synthetic control method (SCM) model, this study calculated the treatment effects of the PVPA policy. The analysis revealed that the policy did not significantly increase rural residential income at the county level. The insignificant treatment effects reflect a weak policy implementation. The PVPA policy tries to synergize the energy-climate-poverty nexus, requiring the coordination of various stakeholders and departments. Meanwhile, governance theory highlights the multivariate character of policy and considers the role of multiple social actors. Therefore, it is necessary to explore the governance factors when the policy implementation is weak. Further investigation of the PVPA projects reveals that the main governance challenges include insufficient motivation, information asymmetry, conflicts of interest, renewable energy curtailment, and the absence of proper maintenance and benefit distribution mechanisms. Considering the principles of good governance, recommendations for enhancing the effectiveness of the PVPA policy are proposed.

Luminescent Organic Triplet Diradicals as Optically Addressable Molecular Qubits.

Optical-spin interfaces that enable the photoinitialization, coherent microwave manipulation, and optical read-out of ground state spins have been studied extensively in solid-state defects such as diamond nitrogen vacancy (NV) centers and are promising for quantum information science applications. Molecular quantum bits (qubits) offer many advantages over solid-state spin centers through synthetic control of their optical and spin properties and their scalability into well-defined multiqubit arrays. In this work, we report an optical-spin interface in an organic molecular qubit consisting of two luminescent tris(2,4,6-trichlorophenyl)methyl (TTM) radicals connected via the meta-positions of a phenyl linker. The triplet ground state of this system can be photoinitialized in its |T0⟩ state by shelving triplet populations as singlets through spin-selective excited-state intersystem crossing with 80% selectivity from |T+⟩ and |T-⟩. The fluorescence intensity in the triplet manifold is determined by the ground-state polarization, and we show successful optical read-out of the ground-state spin following microwave manipulations by fluorescence-detected magnetic resonance spectroscopy. At 85 K, the lifetime of the polarized ground state is 45 ± 3 μs, and the ground state phase memory time is Tm = 5.9 ± 0.1 μs, which increases to 26.8 ± 1.6 μs at 5 K. These results show that luminescent diradicals with triplet ground states can serve as optically addressable molecular qubits with long spin coherence times, which marks an important step toward the rational design of spin-optical interfaces in organic materials.

A Two-Stage Evaluation of China’s New Energy Industrial Policy Package

Energy structural transformation plays a strategically important role in achieving the dual-carbon reduction goals. Among the various approaches to carbon reduction, the Chinese government regards the growth of the new energy industry as an essential means. Considering that the government policy support determines the long-term growth of the new energy industry, how to improve and optimize the policy support system has always been the core issue. Based on the fact that policy evaluation is a prerequisite, and the new energy industrial development requires the government to promote solutions in the form of a policy package rather than just individual policies, we investigate whether the implementation of the new energy industry policy package (NEIPP) is effective through an empirical case study of Shanghai. A two-stage evaluation method, which integrates the content analysis method (CAM) and synthetic control method (SCM), was used to empirically evaluate the actual effect of the NEIPP. At Stage One, four policy goals were summarized. SCM was used to identify the pure multi-effect of the NEIPP. The results showed that the NEIPP had a significant positive effect on green economic growth and industrial structure, while having a negative effect on carbon emissions. The NEIPP had no impact on the promotion of technological innovation. Several policy implications were drawn from this study.

Increasing intergovernmental coordination to fight crime: evidence from Mexico

Abstract Latin America is the most violent region in the world, with many countries also suffering from high levels of criminality and the presence of powerful criminal organizations. Identifying government responses that improve citizen security is imperative. Existing research argues that improving intergovernmental coordination helps the state combat criminality, but has limited its analysis to political factors that affect coordination. I study the impact of increasing intergovernmental coordination between law enforcement agencies. Using the generalized synthetic control method, original data on the staggered implementation of a police reform that increased intergovernmental police coordination and detailed data on criminal organizations and criminality in Guanajuato, Mexico, I find that the reform weakened criminal organizations and reduced violent crime, but increased violence.

Measuring Price Effects from Disasters Using Public Data: A Case Study of Hurricane Ian

Natural disasters can disrupt housing markets, causing destruction to communities and distress to economic activity. To estimate the effects of disasters on home prices, publicly available data on property damages are often used to classify “treated” properties. However, by design, these data lack precise geospatial information, leading to measurement error in the treatment variable because aggregate measures must be used. We leverage leading difference-in-differences and synthetic control methodologies across various treatments and levels of geography to measure price effects with such data following Hurricane Ian’s unexpected landfall in Southwest Florida during September 2022, coinciding with the state’s initial recovery from the COVID-19 pandemic. Empirical results suggest positive, time-varying price effects, though we place caveats on these results because there may be many mechanisms underway; our results should be interpreted as descriptive correlations and not causal effects for various reasons. Our main contribution is methodological, highlighting the importance of robustness checks, functional form, statistical techniques, and testing across different samples. Additionally, quicker access to high-quality public data could enhance quantitatively informed conversations on natural disaster effects.

The Impact of City-County Mergers: Evidence from Sichuan Province

Municipal mergers are often used to facilitate regional economic development. City-county mergers (CCM) are a form of municipal merger and one of the administrative division adjustment methods adopted by prefecture-level city governments to accelerate regional economic developments in China. Most studies of CCMs have focused on the economic effects of CCMs on prefecture-level cities, and little attention has been paid to the county-level effects post-merger. In this paper, we use the Synthetic Control Method (SCM) to examine the effect of the CCM of Nanxi district (formerly Nanxi county) in Sichuan province. We find that after the CCM, GDP per capita was 1989 yuan higher in 2017 than predicted. We also find that the structure of the local economy was altered toward a more industrialized economy, with a decrease in service and agricultural shares (although only significantly for the industrial and service). There is also evidence that these findings were driven by a larger portion of the local economy that was from private markets, suggesting these reforms incentivized larger private production.

Environmental policies as engines for tourism eco-efficiency: quasi-experimental evidence

Determining the actual effectiveness of environmental policies is paramount for enhancing tourism eco-efficiency. However, few studies have systematically investigated the specific effects of such policies on tourism eco-efficiency. We utilize the slack-based measure data envelopment analysis model to assess tourism eco-efficiency across 30 Chinese provinces from 2003 to 2021. We delve into the environmental policy of China’s Ecological Civilization Pilot Zone, scrutinizing its institutional background and assessing its ramifications for tourism eco-efficiency within the framework of the “Driving forces-Pressure-State-Impact-Response” framework and institutional theory. Moreover, we empirically explore the causal link between this policy and tourism eco- efficiency by adopting the synthetic control and difference-in-differences approaches. Our findings indicate that the implementation of the National Ecological Civilization Pilot Zone policy has led to a 5.16% average enhancement in tourism eco-efficiency. Although significant improvements were observed in Fujian, Jiangxi, and Yunnan, Qinghai experienced a decline, as indicated by the synthetic control method. Furthermore, the impact extends spatially, manifesting both at the local level and as spatial spillover effects on the eco-efficiency of tourism in neighboring regions. These results confirm the policy’s effectiveness and highlight the need for devoting increased attention to economically slower-developing regions in sustainable tourism development.

Effects of SUDENE’s tax incentives on job creation in the Northeast region of Brazil

ABSTRACT This paper analyzes the effects of tax incentives on job creation by companies located in the Northeast region of Brazil, disaggregated by sector. The generalized synthetic control method is employed to handle this problem. The evidence indicates that the incentives have beneficial effects on increasing firm employment. Specifically, we observed positive impacts in the labour-intensive manufacturing sector. Therefore, the results provide positive evidence for using tax incentives for regional development, although the effects are concentrated in the manufacturing sector.

Does implementing opt-out solve the organ shortage problem? Evidence from a synthetic control approach

Does implementing opt-out solve the organ shortage problem? Evidence from a synthetic control approach

The Impact of the Opportunity Zone Program on Residential Real Estate

Problem definition: Opportunity zones (OZs) are designated census tracts in which real estate investments can gain tax benefits. Introduced by the U.S. Tax Cuts and Jobs Act of 2017, the goal of the OZ program is to foster economic development in distressed neighborhoods. In this paper, we investigate and optimize the OZ selection process and examine the impact of OZs by exploiting two data sets: a proprietary real estate data set that includes 36.1 million residential transactions spanning all 50 U.S. states and census-tract demographics data between 2010 and 2019. Methodology/results: We show that census tracts with higher poverty and unemployment rates were more likely to be selected. Counterintuitively, however, tracts with a higher average real estate price were also more likely to be selected. We then apply difference-in-differences, synthetic control, and matching techniques to rigorously assess the impact of the OZ program on two key real estate metrics: price and transaction volume. We find that the OZ program increased real estate prices by 4.03%–6.13% but do not observe a significant effect on the transaction volume. We also find that investors primarily targeted the high-end real estate market, namely, exhibiting a cherry-picking behavior. To better fulfill its intended societal and economic goals, we propose an optimization framework with fairness considerations for OZ assignment decisions. We show that the OZs assigned from our fairness-aware optimization formulation can better serve distressed communities and mitigate investors’ cherry-picking behavior. Managerial implications: Our paper underscores the importance of incorporating fairness in OZ designation to achieve a desirable real estate market reaction. Our large-scale empirical analysis provides a comprehensive assessment of the current government OZ assignment, and our fairness-aware optimization framework provides concrete recommendations for policy makers. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.0746 .

TigerBase: A DNA registration system to enhance enforcement and compliance testing of captive tiger facilities

The illegal trade in tigers (Panthera tigris) and their derivatives, such as bones, teeth and pelts, is a major threat to the species’ long-term persistence. As wild tiger populations have dwindled, a large proportion of trafficked tiger products now derive from captive breeding facilities found throughout Asia. Moreover, wild tigers have been poached and laundered into captive facilities, then falsely designated as captive-bred. The establishment of a DNA registration system is recognized as a key tool to monitor compliance of captive facilities, support tiger trade investigations and improve prosecution outcomes. Here, we present a standardised wildlife forensic DNA profiling system for captive tigers called TigerBase. TigerBase has been developed in four South-East Asia countries with captive tiger facilities: Malaysia, Vietnam, Thailand and Lao PDR. TigerBase DNA profile data is based on 60 single nucleotide polymorphism (SNP) markers, genotyped using two different TaqMan®-based approaches: OpenArray® chip (capable of genotyping 60 SNPs for 48 samples in a single chip), and singleplex TaqMan® assays (capable of genotyping one SNP for one sample per reaction). Of the 60 SNPs, 53 are autosomal nuclear markers, suitable for individualisation and parentage applications, two are sex-linked markers, suitable for sexing, and five are mtDNA markers, suitable for maternal subspecies identification. We conducted a series of validation experiments to investigate the reliability and limitations of these SNP genotyping platforms. We found that the OpenArray® chip platform is more appropriate for generating reference data given its greater throughput, while the singleplex TaqMan® assays are more appropriate for genotyping lower quality casework samples, given their higher sensitivity and throughput flexibility. Only 19 autosomal nuclear markers were validated as singleplex TaqMan® assays, which generally provides ample power for individualisation analysis (probability of identity among siblings was <6.9 ×10−4), but may lack power for specific parentage questions, such as determining parentage of an offspring when one of the parent’s genotypes is missing. Further, we have developed pipelines to support standardised SNP calling and decrease the chance of genotyping errors through the use of analytical workflows and synthetic positive controls. We expect the implementation of TigerBase will enhance enforcement of tiger trafficking cases and encourage compliance among captive tiger facilities, together contributing to combatting the illegal tiger trade.

Opting out of an EU identity? The effects of differentiated integration on European identity

ABSTRACT The link between European institutions and European identities remains under-explored. Similarly, we know little about how countries opting out of European integration has helped shape their citizens’ view of themselves as more or less European. Using general synthetic control models and data from 1983 to 2020, I find that people in countries with opt-outs tend to identify as more strongly European in the years after an opt-out is implemented, and most prominently so in the countries where opt-outs responded to a popular demand and were associated with great politicisation. This shows that providing individual countries with greater autonomy may strengthen their citizens’ attachment to Europe, but that any such effect is likely to depend on domestic variations in for instance elite politicisation of European integration.

The impact of renewable energy consumption and energy poverty on pollution in Central and Eastern European countries

Considering the actual climate challenges, pollution should be reduced in Central and Eastern European countries (CEECs) from the European Union (EU). The main objective of this paper is to assess the impact of energy poverty and renewable energy consumption (REC) on pollution in 10 CEE countries, EU member states, during 2005–2022. The results based on the synthetic control method suggested that Renewable Energy Directive implemented in 2009 contributed to the decrease in the level of CO2 emissions in each CEEC compared to the states in this region that are not EU member states (Albania, Serbia, Moldova, North Macedonia, Georgia, Montenegro, Belarus, Ukraine). The panel regression analysis based on MG estimator showed that energy poverty enhanced CO2 emissions, while renewable energy consumption reduced it and had a mediating effect on the impact of energy poverty on pollution in the CEECs. The population unable to keep home warm, foreign direct investment and value added in industry had an asymmetric effect on CO2 emissions in the CEECs as method of moments quantile regressions suggest. These results are subject to policy proposals to tackle both pollution and energy poverty in the region.

Evaluating Policy Efficacy in Higher Education: A Synthetic Control Analysis of Ecuador’s Higher Education Law on Research Productivity

Background: This paper investigates the impact of Ecuador’s Ley Orgánica de Educación Superior (LOES), enacted in 2010, which mandated comprehensive reforms in higher education. Objective: The objective of this study is to determine whether the implementation of the LOES has led to a significant increase in academic publications in Ecuador, thereby contributing to sustainable educational practices and aligning with the Sustainable Development Goals (SDGs). In this context, sustainability refers to the ongoing capacity of higher education institutions to generate research that contributes to the long-term development of knowledge, aligns with global sustainability goals, and ensures educational practices that are responsive to societal needs. Methods: Using a synthetic control method, this study evaluates the impact of the LOES on the number of academic publications recorded in Scopus. A synthetic control consisting of data from countries with similar educational and economic profiles serves as a counterfactual to Ecuador’s situation. Results: Before the LOES, the average annual number of publications was stable at 253.4 per year. Post-2010, this number surged, reaching an average of 3645.84 publications per year, representing a 358.41% increase. By 2023, the actual number of publications in Ecuador rose to approximately 6584, significantly surpassing the synthetic control estimate of 1431 publications. Conclusions: The findings confirm that the LOES has been effective in increasing research output and advancing educational sustainability in Ecuador. This analysis not only contributes to the literature on the impact of educational policies but also demonstrates the utility of synthetic control methods in assessing policy effectiveness, underscoring the potential of targeted interventions to promote academic excellence and sustainability in education.

Tax incentives and environmental performance: The pay-as-you-throw policy in Emilia-Romagna, Italy

This study investigates the impact of implementing the pay-as-you-throw policy as a fiscal incentive mechanism for municipal waste management across municipalities in the Emilia-Romagna region, Italy. Utilizing panel data from 2010 to 2022 and employing a synthetic control with staggered treatment adoption, we evaluate the policy's effects on environmental and local public finance performances. Our findings reveal that treated municipalities witness an average 10% increase in separate waste collection alongside a parallel reduction in municipal waste production since the policy outset, equating to approximately 60 kg per capita annually. Furthermore, our analysis indicates that the policy enables local governments to reduce current energy and environmental expenditures by roughly €130 per capita annually in our optimal model. Notably, results hold robust across three recently developed estimators using difference-in-differences with staggered treatment adoption over time. The policy proves overall effectiveness in promoting circularity within municipal waste management systems, leading to better environmental performances, and decreased environmental management expenses. These implications underscore the potential value for local governments to adopt similar strategies where not yet envisaged.

Indian Buffet process factor model for counterfactual analysis

This article proposes a factor model-based counterfactual analysis. We explicitly estimate the underlying factor structure of the outcome variables and estimate the counterfactual values of the unit subject to an intervention. With the help of the non-parametric Bayesian Indian Buffet Process prior, our approach is capable of exploring heterogeneous factor exposures, and the number of latent factors is endogenously determined in the estimation process. The flexible Markov Chain Monte Carlo algorithm utilizes the maximal intervention-free information provided by the data, whereas the original synthetic control only uses pre-intervention data. The counterfactual values are estimated by simulating from the posterior predictive distribution so that we can integrate out any parameter estimation uncertainty. We also calculate the posterior predictive upper- and lower-quantile bounds for inference. The two applications, namely California’s Tobacco Control Program and the West German Reunification, demonstrate the usefulness of our approach compared to the synthetic control method and the elastic net model. The Monte Carlo simulation study also shows the robustness of our approach with respect to nonlinear dynamics in the underlying factor process.

Resistance of Doubled Haploid Rice Lines with Green Super Rice Characters to Bacterial Leaf Blight

&lt;p&gt;Bacterial leaf blight (BLB), caused by &lt;em&gt;Xanthomonas oryzae&lt;/em&gt; pv. &lt;em&gt;oryzae&lt;/em&gt; (&lt;em&gt;Xoo&lt;/em&gt;) is a significant disease attacking rice crops worldwide. This disease attacks at various stages of plant growth and causes significant yield loss. Breeding new varieties resistant to BLB is important to support sustainable agriculture in the future. This study aimed to identify new superior green super rice (GSR) lines resistant to BLB disease. The experiment evaluated the resistance of lowland rice lines obtained from anther culture using a factorial randomized complete block design. The 1&lt;sup&gt;st&lt;/sup&gt; factor was genotype, consisting of 20 lines, 2 checks of commercial varieties (Inpari 42 Agritan GSR and Inpari 18), a resistant check (Conde), and a susceptible check (Taichung Native 1). The 2&lt;sup&gt;nd&lt;/sup&gt; factor was BLB pathotypes (i.e., III, IV, and VIII). Quantitative data on disease severity and severity index were analyzed using analysis of variance and t-Dunnett test at 5% level. The results showed that the interaction between genotype and pathotype affected the disease severity and severity index in both growth phases. The tested lines exhibited varying resistance, from susceptible to resistant, to BLB. Four lines (SN 11, 13, 57, and 58) showed moderate to resistant criteria for BLB disease of 3 pathotypes in both growth phases. The selected lines can be used as a source of parents for breeders and candidates for new superior varieties with BLB resistance properties to support the reduction of synthetic chemical bactericide inputs and control BLB disease. However, further field evaluations are necessary to assess their performance.&lt;/p&gt;

Optimal initial donor selection for the synthetic control method

This paper argues that the performance of the Synthetic Control Method (SCM) can depend on the initial set of control units (donors) due to a bias–variance trade-off. A forward stepwise selection algorithm, validated via cross-validation, may reduce prediction error by suggesting to use fewer donors.

Revisiting the Occupational Health Impact of Right-to-Work Laws: A Research Note.

This research note reevaluates the occupational health impact of right-to-work (RTW) legislation, incorporating recent developments in causal inference techniques. In an era marked by an uptick in the adoption of anti-union legislation and increases in workplace fatalities and injuries, it is particularly urgent to examine the extent to which RTW laws affect workers' health. Using a state-year-level dataset spanning 28 years and collected from multiple data sources, we apply an innovative generalized synthetic control method to overcome several limitations of the traditional two-way fixed-effects approach to examine the effect of RTW laws on occupational fatal injuries as well as various other health outcomes. Robustness checks were conducted using a wide range of alternative methods for two-way fixed-effects adjustments. In contrast with findings from previous studies, we found null effects on occupational fatal injuries, as well as on all other health outcomes. Overall, our results indicate that findings from previous studies are based on very thin empirical evidence, with potentially underestimated standard errors and unobserved confounders. Our results highlight the importance of revisiting research questions using updated methodological tools.

Disability Benefit Reform and Benefit Outcomes: A Re-examination of the Introduction of the UK Personal Independence Payment Using Linked Population Data

ObjectivesMany countries face the problem of how to provide support for additional costs faced by disabled people while restricting disability benefit program growth given tight public finances. In 2013, the UK reformed its main additional costs disability benefit with this objective, changing both medical screening and payment rates with the introduction of the Personal Independence Payment (PIP). This study uses newly available linked administrative population data to examine the impact of this major reform on disability benefit receipt. ApproachWe use the newly available 2011CBI dataset, which links Census records to microdata on benefit receipt for the population of England and Wales from 2011-2015. Difference-in-difference and synthetic control methods are used to estimate the reform impact on the probability of flowing onto disability benefits, exploiting the structure of the roll-out of PIP’s introduction across English regions. ResultsIntroducing PIP led to a sharp fall in the probability of disability benefit onflow, with tentative evidence of a partial reversal in the following year. Further analysis is required to quantify the extent to which this reflects well-known administrative delays in processing applications as opposed to a step change in the probability of claims being successful. ConclusionsThis study is the first to present linked administrative population data estimates of the benefit recipiency effects of the introduction of PIP. In doing so it both contributes to the wider international literature on disability benefit reform and provides an early research application of a significant new administrative dataset for England and Wales.