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In this survey we discuss the recent causal panel data literature. This recent literature has focused on credibly estimating causal effects of binary interventions in settings with longitudinal data, emphasising practical advice for empirical researchers. It pays particular attention to heterogeneity in the causal effects, often in situations where few units are treated and with particular structures on the assignment pattern. The literature has extended earlier work on difference-in-differences or two-way fixed effect estimators. It has more generally incorporated factor models or interactive fixed effects. It has also developed novel methods using synthetic control approaches. [ABSTRACT FROM AUTHOR]

In 2019, New York State passed bail reform legislation that limited the use of money bail and expanded pretrial release. The bail reform law took effect on January 1, 2020. We evaluated the effect of this law on crime rates in New York State. Interrupted time series analyses (ITSA) were used to examine whether the bail reform was significantly associated with a crime increase. When a significant association was detected, we examined whether this relationship was causal. The causal relationship was tested using synthetic control methods (SCM). We found that the rates of murder, larceny, and motor vehicle theft increased after the bail reform. We then employed SCM to create a comparison group to control for potential confounders like the pandemic. By comparing New York State with its synthetic control, we found the increases in the murder rate, larceny rate, and motor vehicle theft rate were not statistically significant. Our findings suggest that the effect of bail reform on crime rate increases is negligible. [ABSTRACT FROM AUTHOR]

Using synthetic control methods, we examined the economic effects of political uncertainty. We show that political uncertainty resulting from certain political events is negatively related to major stock indices. Particularly in emerging countries, political turmoil involving the president enormously increases the difficulty of doing business due to increased uncertainty in economic policy. Our results suggest that the beginning of the impeachment process and successful military coup could positively influence the stock market, while a military coup failure and an aircraft accident negatively influence the stock market. Therefore, market investors and business owners in emerging countries must be prepared for significant changes in the progress of a company, industry or sector after the event occurs. [ABSTRACT FROM AUTHOR]

We evaluate the impact of foreign direct investment (FDI) in the forestry sector on regional economic development. We study the effects of the construction and operation of a paper mill on development in the department of Río Negro, Uruguay. This paper contributes to the literature on impact evaluations of FDI in the forestry industry in developing countries at the regional level. Applying synthetic control methods, we find positive and statistically significant effects of the investment project on per capita departmental gross value added (GVA), and on main occupation income of the inhabitants of Río Negro. [ABSTRACT FROM AUTHOR]

In order to develop green finance and realize the coordinated development of environment and economy, China set up green finance reform and innovation pilot zones in 2017. Taking the establishment of green finance reform and innovation pilot zones in China as an exogenous shock and based on the synthetic control method, this paper explores the impact of the pilot policies on green innovation vitality by taking five pilot provinces as the experimental group and 25 provinces without pilot policies as the control group. It is found that the pilot policy significantly enhances the level of green innovation dynamism in the pilot regions, but due to the different policy focuses, the innovation effect is immediate in Zhejiang, Guangdong, Guizhou, and Jiangxi, while the policy effect is significantly lagging behind in Xinjiang; government incentives are an important channel through which the policy enhances the green innovation dynamism; and the above findings are more significant in the samples of substantial green innovation dynamism and the eastern region. In addition, the extended economic consequences analysis shows that the pilot policy can significantly improve energy efficiency in the pilot region with a significant time lag. The findings of the study not only provide empirical evidence for the implementation effect of the green finance pilot policies, but also have practical implications for improving the green finance system and replicating and extending the green finance reform and innovation pilot zones. [ABSTRACT FROM AUTHOR]

We consider a budget hotel chain's revenue management problem of deciding how to dynamically allocate capacity to multiple segments of customers. Our work solves an industrial‐sized problem faced by practitioners, with the reality of implementation motivating us to develop a tailored reinforcement learning approach. Our approach proceeds in two steps. First, a recommended average discount is computed with a reinforcement learning algorithm. Then, the recommended average discount is turned into a capacity allocation through a linear program. This approach overcomes the challenges of characterizing demand and estimating cancellations, and it facilitates hotel managers' acceptance of the revenue management system. We implement this approach in the hotel chain in a pilot study and assess its effectiveness using synthetic control methods. Our approach improves the key operational performance measure—revenue per available room—by 11.80%. There is heterogeneity in how the pilot hotels improve their revenue per available room. Some mainly increase their occupancy rate, some mainly increase the average daily room rate, while others experience significant increases in both. Further analysis shows that our approach uncovers the individual sources of suboptimal performance in pilot hotels and correspondingly improves decision‐making. Our work demonstrates that a reinforcement learning approach for hotel revenue management is promising. Highlights: We develop a reinforcement learning approach to solve a budget hotel chain's revenue management problem of deciding how to dynamically allocate capacity to multiple segments of customers.This approach overcomes the challenges of characterizing demand and estimating cancellations, and it facilitates hotel managers' acceptance of the revenue management system.We implement this approach in the hotel chain in a pilot study and show that it improves the revenue per available room by 11.80% using the synthetic control method. [ABSTRACT FROM AUTHOR]

Public funding to higher education has declined over the years and many states have experimented with policies to encourage private sector donations to public universities. Building on research that examines the intersection of state policy and philanthropy, we examine the influence of a state policy on endowment gifts to the University of Wyoming (UW). Wyoming sought to support institutional advancement efforts by matching private gifts that were at least $50,000 in value. We use synthetic control methods (SCM) to analyze data from the Integrated Postsecondary Data System (IPEDS) and test whether the policy increased endowment growth of the university between 2001 and 2018, relative to similar universities. We find limited evidence that the state policy led to long-term growth in UW's endowment that was proportionally larger than a counterfactual synthetic control. We discuss implications for research, state policy, and higher education philanthropy. [ABSTRACT FROM AUTHOR]

Many college athletes suffer career-ending injuries that leave them with expensive medical bills and lost scholarship opportunities. California's 2012 student athlete bill of rights mandated that the state's universities continue to care for college athletes by providing access to medical care and equivalent scholarships even if they were injured and could no longer participate in athletics. We analyzed publicly available data from the college athletics financial information database using multiple quasi-experimental approaches, including difference-in-differences with propensity score weights and synthetic control methods. We found evidence that Cal-Berkeley and UCLA increased medical expenditures but not student aid. Our findings were robust across both types of analyses. We discuss implications and offer directions for future research related to policy implementation. [ABSTRACT FROM AUTHOR]

So far, empirical research on an ex-post benchmark of the euro adoption has relied on the synthetic control method by Abadie & Gardeazabal (Am Econ Rev 93:112-132, 2003) and Abadie et al. (J Am Stat Assoc 105:493-505, 2010, Am J Polit Sci, 59:495-510, 2015). However, the evidence obtained with this method is not overly consistent, leading to the conclusion that the method is not too robust to different settings of the adjustment screws. Using a new method developed by Harvey & Thiele (J Appl Econ 36:71–85, 2021) based on structural time series models, I find that France and Italy are clear losers from the euro while there are no real winners until 2019. Spain, Netherlands, Greece gain in the period before the financial crisis, but afterwards they lose. In fact, only the German economy is robust to the two crises but it loses until 2008. Relating the theories of optimum currency areas to the estimated gaps of the euro adopters from their synthetic controls, I find that openness, real convergence, and net migration are the main drivers of gains from a euro adoption, while the main drivers of losses are low levels of competitiveness, fiscal instability and labour market rigidity. Examining the crisis channels of the financial and euro crisis shows that fiscal instability, labour market rigidity and also business cycle synchronization cause large losses during the crises. Net migration helps to dampen these shocks. While openness is beneficial during the pre-crises period, it cannot help dampen the shock of the crises. [ABSTRACT FROM AUTHOR]

This study demonstrates the impact of initial public offerings (IPOs) on local house prices. Applying spatial difference‐in‐differences methods to IPOs in California from 1993 to 2017, we find house prices increase by 0.7%–0.9% near an IPO firm's headquarters around filing and issuing dates. Upon lockup expiration, price changes depend on postissuance returns. Treating the San Francisco Bay as a commuting barrier, we identify sustained price increases after filings and temporary increases after issuing and lockup expiration. We also confirm post‐IPO price divergence between the treatment and synthetic control areas. Our findings indicate the effect of liquid wealth under mild financial constraints. [ABSTRACT FROM AUTHOR]

Background: Traditional epidemiologic approaches such as time-series or case-crossover designs are often used to estimate the effects of extreme weather events but can be limited by unmeasured confounding. Quasi-experimental methods are a family of methods that leverage natural experiments to adjust for unmeasured confounding indirectly. The recently developed generalized synthetic control method that exploits the timing of an exposure is well suited to estimate the impact of acute environmental events on health outcomes. To demonstrate how this method can be used to study extreme weather events, we examined the impact of the 20-26 October 2007 Southern California wildfire storm on respiratory hospitalizations.Methods: We used generalized synthetic control to compare the average number of ZIP code-level respiratory hospitalizations during the wildfire storm between ZIP codes that were classified as exposed versus unexposed to wildfire smoke. We considered wildfire exposure eligibility for each ZIP code using fire perimeters and satellite-based smoke plume data. We retrieved respiratory hospitalization discharge data from the Office of Statewide Health Planning and Development. R code to implement the generalized synthetic control method is included for reproducibility.Results: The analysis included 172 exposed and 578 unexposed ZIP codes. We estimated that the average effect of the wildfire storm among the exposed ZIP codes was an 18% (95% confidence interval: 10% to 29%) increase in respiratory hospitalizations.Conclusions: We illustrate the use of generalized synthetic control to leverage natural experiments to quantify the health impacts of extreme weather events when traditional approaches are unavailable or limited by assumptions. [ABSTRACT FROM AUTHOR]

The literature highlights that inflation targeting (IT) economies enjoy a sizeable share of global trade, suggesting IT is a comparative advantage exclusive to such countries. Using a set of developed and developing countries—coupled with synthetic control methods—we estimate the causal effect of IT on the volume of international trade. We compare the post-IT path of each treated country to its synthetic counterpart. We find that IT adoption had sizeable positive (negative) long-run effects on Mexico's (Brazil's) trade and short-run effects, as large as 11 percentage points, on Uganda's trade. For treated countries in Asia, Thailand recorded increases in trade, whereas the Korea Republic experienced nonlinear IT-induced trade effects. Norway registered negative IT effects, and Sweden, Canada, New Zealand and the UK experienced nonlinear effects in the post-IT period. IT induced negative and positive import and export volume and price changes in additional targeters. These heterogeneous IT-induced changes suggest that IT is not a source of comparative advantage in trade for all targeters and all post-adoption years. [ABSTRACT FROM AUTHOR]

The establishment of marine ranching demonstration areas is crucial for restoring offshore fishery resources, fostering ecosystem harmony, and creating blue "carbon sinks" in China. While their ecological benefits are evident, their impact on surrounding areas remains uncertain. This study takes the first batch of national marine ranching demonstration areas established in 2015 as a quasi-natural experiment and uses synthetic control methods to empirically evaluate the effects and mechanisms of their construction on regional ecological efficiency. Results show heterogeneous impacts, with positive effects in Jiangsu and Liaoning but negligible elsewhere. Mechanism analysis reveals that marine ranching demonstration areas enhance ecological efficiency through economic growth, and industrial structure optimization. Differences in marine ranching types and regulations influence their impact, with public welfare-oriented marine ranching showing greater positive effects compared to aquaculture-oriented ones. Overall, these findings hold theoretical and practical implications for advancing modern marine ranching construction. [Display omitted] • The impact of the construction of marine ranching on regional eco-efficiency is investigated. • Super-SBM model and synthetic control methods are used in the research. • Findings reveal heterogeneous effects across regions, with significant improvements observed in Jiangsu and Liaoning. • Two mechanisms, namely economic outputs increasing and industry structure optimizing are identified. • Provide important references for future marine ranching construction. [ABSTRACT FROM AUTHOR]

It is becoming increasingly popular in applications of standard synthetic control methods to include the entire pretreatment path of the outcome variable as economic predictors. We demonstrate both theoretically and empirically that using all outcome lags as separate predictors renders all other covariates irrelevant in such settings. This finding holds irrespective of how important these covariates are for accurately predicting posttreatment values of the outcome, threatening the estimator's unbiasedness. We show that estimation results and corresponding policy conclusions can change considerably when the usage of outcome lags as predictors is restricted, resulting in other covariates obtaining positive weights. Monte Carlo studies examine potential bias. [ABSTRACT FROM AUTHOR]

Abstract Background A country’s spending on healthcare significantly improves its population health status. No comparative study has examined how the threat perceived by leaders influences health expenditure and cross-national analyses of authoritarian regimes. The objectives of this study are to examine how time horizons of autocrats influence health expenditure. Methods We designed a mixed methods research approach. First, the study used panel data from 1995 to 2010 covering 95 countries (n = 1208) and applied fixed effects regression models. As a proxy for time horizons, the study generated the predicted survival time for each regime-year using parametric survival analysis and the predictors to model regime failure. Second, we chose Chad, Rwanda and Ivory Coast to apply synthetic control methods for comparative case studies. Armed conflict had significant effects on regime duration and was used for an intervention. We constructed a synthetic version of each country, combining counties that did not or did experience armed conflict to resemble the values of health expenditure predictors for the actual country prior to the intervention. Results We found that an increase in the natural log form of survival time by 1 resulted in a 1.14 percentage point increase in health expenditure (% of GDP) (1.14, 95% CI = 0.60–1.69). Furthermore, we found that the difference in health expenditure between the actual Chad and its synthetic version starts to grow following the civil war in 2004 (in 2004, actual: 5.72%, synthetic: 5.91%; in 2005, actual: 3.91%, synthetic: 6.74%). Similarly, a large health expenditure gap between the actual Rwanda and its synthetic control resulted after the peace deal was signed in 2002 (in 2002, actual: 4.18%, synthetic: 4.77%; in 2003, actual: 6.34%, synthetic: 5.03%). In Ivory Coast, the two series diverge substantially during the civil war from 1999 to 2005 (in 1998, actual: 7.30%, synthetic: 7.11%; in 2002, actual: 4.47%, synthetic: 7.43%; in 2007, actual: 6.35%, synthetic: 6.50%). Conclusions The findings suggest that health expenditure decreases as regime time horizons shrink, and reducing armed conflict is a way to promote regime stability.

2020 broke records for the most active fire year on the West Coast, resulting in the worst air quality observed in decades. Concurrently, the public health threat of COVID-19 caused over 1 million deaths in the United States (US) and Mexico in 2020 and 2021. Due to the effect of air pollution on respiratory diseases, wildfire-specific particulate matter is a hypothesized driver of COVID-19 severity and death. Capitalizing on wildfire smoke that hit the San Diego-Tijuana border region in September 2020, we applied synthetic control methods to explore its potential differential role in affecting COVID-19 mortality on both sides of the border. Daily data on COVID-19 cumulative deaths for US counties were obtained from the CDC COVID tracker and data for Mexican municipalities was obtained from the Mexican Secretary of Health. Counties and municipalities with wildfire smoke exposure were identified using the National Oceanic and Atmospheric Administration hazard mapping smoke product (HMS); a day where 90% of the area was covered by smoke was considered exposed for the main analyses. Unexposed counties/municipalities were considered as potential controls. The San Diego-Tijuana border region was covered by dense smoke by the 7th of September; 707 COVID-19 deaths had occurred in San Diego and 1367 in Tijuana. While a slight increase in cumulative mortality was observed in San Diego, no change was found in Tijuana; neither estimate indicated a strong precise effect of wildfire smoke on COVID-19 mortality. We hope this study will serve as an illustration of how border contexts can be used to investigate differential vulnerability to wildfire smoke for infectious diseases. Examining the interactive effect of COVID-19 and smoke can help in recognizing the implications of these dual health risks which will be increasingly important as wildfires become more frequent and severe in the context of climate change.

In this paper, we explore the role of trade in the evolution of labor share in Latin American countries (LAC). We use trade agreements with large economies (US, EU, and China) to capture the effect of sharp changes in trade. During the last two decades, the countries that signed these trade agreements experienced a negative trend in labor share, while in the remaining countries there is an average increase in this share, generating a gap of 7 percentage points. We apply synthetic control methods, combined with regression analysis, to estimate the average causal impact of trade agreements on labor share. While effects are heterogeneous in our eight case studies, the average impact is negative between 2 to 4 percentage points of GDP four years after the entry into force of the trade agreements. This result is robust to the specification used and to the set of countries in the donor pool. We find that trade agreements with more labor-abundant counterparts affect labor share more, in line with traditional Heckscher–Ohlin forces. We also find that, after trade agreements, exports of manufactured goods and the share of industry to GDP increase on average, most notably in the case studies where negative effects on labor share are significant, a fact compatible with enhanced participation in Global Value Chains. Finally, a decomposition shows that all the reduction in labor share is explained by a negative impact on real wages. • Since 1994 Latin American countries signed trade agreements with US, EU, and China • We use Synthetic Control to identify the effects of trade agreements on labor share • After implementing trade agreements, there is a reduction in labor share • We show that the fall in average real wages explains all the effect • Effect relates to counterpart's factor abundance, and rising manufacturing exports [ABSTRACT FROM AUTHOR]

Abstract Background Scholars have long been sceptical about the effectiveness of human rights treaties in changing the behaviour of states parties and prior empirical research has often justified that scepticism. However, only a few prior studies have considered the effects of adoption of core human rights treaties on health outcomes and only one prior study has analysed the effects of adoption of the Convention on the Rights of the Child (CRC) on children’s health outcomes. Methods In this study, we estimated the effects of CRC adoption on child mortality rates and vaccination rates in less developed countries. In particular, we compared 43 less developed countries that adopted the CRC in 1990 with synthetic control groups drawn from 21 less developed countries that adopted it after 1992. Results We find that CRC adoption may be related to additional reductions in infant and under-5 mortality rates of about 1 to 2 deaths per 1000 live births, on average, during the first three years after adoption, although those relationships are not statistically significant. And we find that CRC adoption is related to additional increases in vaccination rates for the five vaccines that we considered of about 4 to 5%, on average, during the first three years after adoption and that those relationships remain significant for up to seven years after adoption. Conclusion From a policy perspective, our results further support the effectiveness of CRC adoption in promoting children’s right to health in less developed countries. And from a research perspective, our results show the advantages of using synthetic control methods in these types of studies, because our analyses using other methods that have most commonly been used in these studies did not find any consistent, significant relationships between CRC adoption and mortality or vaccination rates.

The R package microsynth has been developed for implementation of the synthetic control methodology for comparative case studies involving micro- or meso-level data. The methodology implemented within microsynth is designed to assess the efficacy of a treatment or intervention within a well-defined geographic region that is itself a composite of several smaller regions (where data are available at the more granular level for comparison regions as well). The effect of the intervention on one or more time-varying outcomes is evaluated by determining a synthetic control region that resembles the treatment region across pre-intervention values of the outcome(s) and time-invariant covariates and that is a weighted composite of many untreated comparison regions. The microsynth procedure includes functionality that enables its user to (1) calculate weights for synthetic control, (2) tabulate results for statistical inferences, and (3) create time series plots of outcomes for treatment and synthetic control. In this article, microsynth is described in detail and its application is illustrated using data from a drug market intervention in Seattle, WA.

Abstract Recently, Abadie et al. (Am J Polit Sci 59:495–510, 2015) have expanded synthetic control methods by the so-called cross-validation technique. We find that their results are not being reproduced when alternative software packages are used or when the variables’ ordering within the dataset is changed. We show that this failure stems from the cross-validation technique relying on non-uniquely defined predictor weights. While the amount of the resulting ambiguity is negligible for the main application of Abadie et al. (Am J Polit Sci 59:495–510, 2015), we find it to be substantial for several of their robustness analyses. Applying well-defined, standard synthetic control methods reveals that the authors’ results are particularly driven by a specific control country, the USA.

As one of the most important transportation infrastructure between cities, high-speed rail (HSR) not only had a huge economic effect on the cities along the route, but also had a certain effect on the economic disparity between cities. Based on the panel data of 40 prefecture-level cities along the main railway in China from 2001 to 2017, the economic effect of HSR is investigated by synthetic control methods (SCM) in this paper. The results show that HSR had the strongest significant positive economic effect on the city with higher economic development level and speed, had significant negative economic effect on the city that facing a negative economic growth, had insignificant weak positive economic effect on the city with lower economic development level and speed. Thus the economic effect of HSR had strong disparity. In addition, in order to explore the reasons for the economic effect disparity of HSR, this study further analyzed the mechanism of the disparity. It is found that the indirect economic effects (accelerating the flow efficiency of factors of production and changing the distribution of factors of production) brought by HSR had positive economic effects in certain cities, but had negative economic effects in some others. And it was the main reason for the economic effect disparity of HSR. By contrast, the direct economic effects of HSR (promoting the development of traffic consumption and tourism industry) often only had positive economic effects, and showed strong consistency in different cities. • This paper constructed a new evaluation framework to investigate the mechanism of HSR's economic effect and its disparity. • The results show that economic effect of HSR had strong disparity in cities with different economic condition. • The indirect economic effects brought by HSR was the main reason for HSR's economic effect disparity. • The direct economic effects of HSR showed strong consistency in different cities. [ABSTRACT FROM AUTHOR]

Carbon trading is an effective market emission reduction mechanism. In order to formulate effective market policy, it is necessary to access a deep understanding of carbon trading policy implementation. So based on the panel data of 30 regions in China from 2001 to 2016, we investigated the factors of carbon emissions through LMDI decomposition approach, and then discuss the effect of policy implementation in eight pilots using synthetic control methods. The main conclusions are as follows: The distribution tendency of carbon emissions in China is obviously high in the east and low in the west, and the proportion of these regions' emissions to the total are respectively around 48.7%, 34.0% and 17.3%. The total carbon emissions effect can be divided into five parts, which respectively are energy structure, energy intensity, economic development, urbanization and population size. The gap between real and synthetic carbon emissions in each pilot is enlarged after implementation. The probability of the real policy effect is 4.35%, which at a 5% significant level refuses the original assumption that there is no policy effect, and shows that the carbon trading policy can effectively reduce emissions and achieve the goal of total control. [ABSTRACT FROM AUTHOR]

Background: A country's spending on healthcare significantly improves its population health status. No comparative study has examined how the threat perceived by leaders influences health expenditure and cross-national analyses of authoritarian regimes. The objectives of this study are to examine how time horizons of autocrats influence health expenditure.Methods: We designed a mixed methods research approach. First, the study used panel data from 1995 to 2010 covering 95 countries (n = 1208) and applied fixed effects regression models. As a proxy for time horizons, the study generated the predicted survival time for each regime-year using parametric survival analysis and the predictors to model regime failure. Second, we chose Chad, Rwanda and Ivory Coast to apply synthetic control methods for comparative case studies. Armed conflict had significant effects on regime duration and was used for an intervention. We constructed a synthetic version of each country, combining counties that did not or did experience armed conflict to resemble the values of health expenditure predictors for the actual country prior to the intervention.Results: We found that an increase in the natural log form of survival time by 1 resulted in a 1.14 percentage point increase in health expenditure (% of GDP) (1.14, 95% CI = 0.60-1.69). Furthermore, we found that the difference in health expenditure between the actual Chad and its synthetic version starts to grow following the civil war in 2004 (in 2004, actual: 5.72%, synthetic: 5.91%; in 2005, actual: 3.91%, synthetic: 6.74%). Similarly, a large health expenditure gap between the actual Rwanda and its synthetic control resulted after the peace deal was signed in 2002 (in 2002, actual: 4.18%, synthetic: 4.77%; in 2003, actual: 6.34%, synthetic: 5.03%). In Ivory Coast, the two series diverge substantially during the civil war from 1999 to 2005 (in 1998, actual: 7.30%, synthetic: 7.11%; in 2002, actual: 4.47%, synthetic: 7.43%; in 2007, actual: 6.35%, synthetic: 6.50%).Conclusions: The findings suggest that health expenditure decreases as regime time horizons shrink, and reducing armed conflict is a way to promote regime stability. [ABSTRACT FROM AUTHOR]

Recent evidence has shown an association between wildfire smoke and COVID-19 cases and deaths. The San Francisco Bay Area, in California (USA), experienced two major concurrent public health threats in 2020: the COVID-19 pandemic and dense smoke emitted by wildfires. This provides a unprecedented context to unravel the role of acute air pollution exposure on COVID-19 severity. A smoke product provided by the National Oceanic and Atmospheric Association Hazard Mapping System was used to identify counties exposed to heavy smoke in summer and fall of 2020. Daily COVID-19 cases and deaths for the United States were downloaded at the County-level from the CDC COVID Data Tracker. Synthetic control methods were used to estimate the causal effect of the wildfire smoke on daily COVID-19 case fatality ratios (CFRs), adjusting for population mobility. Evidence of an impact of wildfire smoke on COVID-19 CFRs was observed, with precise estimates in Alameda and San Francisco. Up to 58 (95% CI: 29, 87) additional deaths for every 1000 COVID-19 incident daily cases attributable to wildfire smoke was estimated in Alameda in early September. Findings indicated that extreme weather events such as wildfires smoke can drive increased vulnerability to infectious diseases, highlighting the need to further study these colliding crises. Understanding the environmental drivers of COVID-19 mortality can be used to protect vulnerable populations from these potentially concomitant public health threats.

Paid media expenditures could potentially increase earned media exposures such as social media posts and other word-of-mouth (WOM). However, academic research on the effect of advertising on WOM is scarce and shows mixed results. We examine the relationship between monthly Internet and TV advertising expenditures and WOM for 538 U.S. national brands across 16 categories over 6.5 years. We find that the average implied advertising elasticity on total WOM is small: 0.019 for TV, and 0.014 for Internet. On the online WOM (measured volume of brand chatter on blogs, user-forums, and Twitter), we find average monthly effects of 0.008 for TV and 0.01 for Internet advertising. Even the categories that have the strongest implied elasticities are only as large as 0.05. Despite this small average effect, we do find that advertising in certain events may produce more desirable amounts of WOM. Specifically, using a synthetic control approach, we find that being a Super Bowl advertiser causes a moderate increase in total WOM that lasts 1 month. The effect on online WOM is larger, but lasts for only 3 days. We discuss the implications of these findings for managing advertising and WOM. [ABSTRACT FROM AUTHOR]

This work aims to provide a comprehensive analysis of the association between high‐speed rail (HSR) operation and tourist arrivals in China. A panel data of 238 prefecture‐level cities from 2003 to 2013 is analyzed, using both system generalized method of moments estimation and synthetic control methods. Nationwide, HSR implementation generates sizable tourist inflows, with stronger effect for international arrivals than for domestic ones. Furthermore, heterogeneous HSR impacts are identified through the lens of urban agglomeration: (a) Connection with core cities is quintessential in channeling international customers to the hinterlands, and (b) national cores and hinterlands benefit prominently whereas regional cores lose from HSR accessibility. [ABSTRACT FROM AUTHOR]

This paper evaluates the economic impact of the $14 billion preparatory infrastructure investments for the 2010 FIFA World Cup in South Africa. We use satellite data on night light luminosity at municipality and electoral district level as a proxy for economic activity, applying synthetic control methods for estimation. For the average World Cup municipality, we find significantly positive, short‐run effects before the tournament, corresponding to a reduction of unemployment by 1.3 percentage points. At the electoral district level, we reveal distinct effect heterogeneity, where especially investments in transport infrastructure are shown to have long‐lasting, positive effects, particularly in rural areas. [ABSTRACT FROM AUTHOR]

We introduce synthetic control methods (SCM) as a forecasting technique. Using (i) as economic predictors solely the outcome itself, i.e. lagged values of the dependent variable, and (ii) lagged time series of the outcome to build the donor pool, we let SCM choose and weight appropriate values in order to come up with a sensible forecast of the US GDP growth. This procedure performs competitively viable compared with alternative forecasting methods. [ABSTRACT FROM AUTHOR]

In light of the dramatic rise in mental health disorders amongst adolescents seen in the past decade across the world, there is an urgent need for robust evidence on what works to combat this trend. This paper provides the first robust evaluation of the impacts on school outcomes of 6-year funding programme (HeadStart) for area-level mental health interventions for adolescents. Exploiting educational administrative data on ten cohorts of state-educated secondary school students, we use the synthetic control method to construct counterfactual outcomes for areas that received the funding. We show that the funding did not affect students' absenteeism or academic attainment, but it prevented around 800 students (c. 10% of students typically excluded yearly) from being excluded in its first year. The transient nature of this effect suggests that sustained funding for intervention may be a necessary but not sufficient condition to maintain programme effectiveness over time. [ABSTRACT FROM AUTHOR]

Military crackdowns often disrupt economic development by exacerbating violence. This paper examines the case of the Mexican Drug War, employing synthetic control methods. To prove causality, I use variation on statewide military operations, as well as the rollout of the war. Findings indicate a decrease in GDP per capita equal to 0.5%, in states with military operations. Determinants by which the Mexican Drug War hampered economic development include a proportional reduction in consumption per capita, and a decline in productive investment of at least 0.3%, driven by a drop of 3.2% in commercial credit granted to businesses. [ABSTRACT FROM AUTHOR]

The R package Synth implements synthetic control methods for comparative case studies designed to estimate the causal effects of policy interventions and other events of interest (Abadie and Gardeazabal 2003; Abadie, Diamond, and Hainmueller 2010). These techniques are particularly well-suited to investigate events occurring at an aggregate level (i.e., countries, cities, regions, etc.) and affecting a relatively small number of units. Benefits and features of the Synth package are illustrated using data from Abadie and Gardeazabal (2003), which examined the economic impact of the terrorist conflict in the Basque Country.

Arab countries signed the Greater Arab Free Trade Area (GAFTA) agreement in 1998, while Algeria only joined in 2005. In this study, I investigate the counterfactual trade that Algeria would have had with its GAFTA trade partners had it joined the agreement in 1998. I employ synthetic control methods (SCM) in the context of the gravity approach to international trade to estimate this counterfactual outcome. The SCM creates the synthetic control unit based on a weighted average of the past characteristics and trade realizations of the countries that signed the GAFTA agreement and compares the counterfactual trade outcome against the actual outcome of the treated unit, Algeria in our case. Estimation results indicate that Algeria's trade with nine GAFTA countries, covering more than 96 % of Algeria's pre-treatment trade, would have improved if Algeria had signed the agreement in 1998. [ABSTRACT FROM AUTHOR]