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A country's national income broadly depends on the quantity and quality of workers and capital. But how well these factors are managed within and between firms may be a key determinant of a country's productivity and its GDP. Although social scientists have long studied the role of management practices in shaping business performance, their primary tool has been individual case studies. While useful for theory-building, such qualitative work is hard to scale and quantify. We present a large, scalable dataset measuring structured management practices at the business level across multiple countries. We measure practices related to performance monitoring, target-setting, and human resources. We document a set of key stylized facts, which we label "the international empirics of management". In all countries, firms with more structured practices tend to also have superior economic performance: they are larger in scale, are more profitable, have higher labor productivity and are more likely to export. This consistency was not obvious ex-ante, and being able to quantify these relationships is valuable. We also document significant variation in practices across and within countries, which is important in explaining differences in the wealth of nations. The positive relationship between firm size and structured management practices is stronger in countries with more open and free markets, suggesting that stronger competition may allow firms with more structured management practices to grow larger, thereby potentially raising aggregate national income., Competing Interests: Competing interests statement:The authors declare no competing interest.

Background: A large fraction of the disease burden in the Italian population is due to behavioral risk factors. The objective of this work is to provide a tool to estimate the impact of preventive interventions that reduce the exposure to smoking and sedentary lifestyle of the Italian population, with the goal of selecting optimal interventions., Methods: We construct a Markovian model that simulates the state of each subject of the Italian population. The model predicts the distribution of subjects in each health status and risk factor status for every year of the simulation. Based on this distribution, the model provides a rich output summary, such as the number of incident and prevalent cases for each tracing disease and the Disability Adjusted Life Years (DALY), used to assess the impact of preventive interventions, and how this impact is shaped in time., Results: This paper focuses on the methodological aspects of the model. The proposed model is flexible and can be applied to estimate the impact of complex interventions on the two risk factors and adapted to consider different cohorts. We validate the model by simulating the evolution of the Italian population from 2009 to 2017 and comparing the output with historical data. Furthermore, as a case-study, we simulate a counterfactual scenario where both tobacco and sedentary lifestyle are eradicated from the Italian population in 2019 and estimate the impact of such intervention over the following 20 years., Conclusions: We propose a Markovian model to estimate how interventions on smoking and sedentary lifestyle can affect the reduction of the disease burden, and validate the model on historical data. The model is flexible and allows to extend the analysis to consider more risk factors in future research. However, we are aware that, given the ever-increasing availability of data, it is necessary in the future to increase the complexity of the model, to be closer to reality and to provide decision-making support to the policy-makers., (© 2024. The Author(s).)

This article investigates the factors that contributed to the proliferation of online COVID skepticism on Twitter across Italian municipalities in 2020. We demonstrate that sociodemographic factors were likely to mitigate the emergence of skepticism, whereas populist political leanings were more likely to foster it. Furthermore, pre-COVID anti-vaccine sentiment, represented by "old truthers" on Twitter, amplified online COVID skepticism in local communities. Additionally, exploiting the spatial variation in restrictive economic policies with severe implications for suspended workers in nonessential economic sectors, we find that COVID skepticism spreads more in municipalities significantly affected by the economic lockdown. Finally, the diffusion of COVID skepticism is positively associated with COVID vaccine hesitancy., (Copyright © 2024 The Authors.)

Program evaluations often investigate complex or multi-dimensional constructs, such as individual opinions or attitudes, by means of ratings. A different interpretation of the same question may affect cross-country comparability, leading to the Differential Item Functioning problem. Anchoring vignettes were introduced in the literature as a way to adjust self-evaluations from this interpersonal incomparability. In this paper, we first introduce a new nonparametric solution to analyse anchoring vignette data, recoding a variable based on a rating scale to a new corrected- variable that guarantees comparability in any cross-country analysis. Then, we exploit the flexibility of a mixture model introduced to account for uncertainty in the response process (the CUP model) to test if the proposed solution is effectively able to remove this reported heterogeneity. This solution is easy to construct and has important advantages compared with the original nonparametric solution adopted with anchoring vignette data. The novel indicator is applied to investigate self-reported depression in an old population. Data that will be analysed come from the second wave of the Survey of Health, Ageing and Retirement in Europe, collected in 2006/2007. Results highlight the need of correcting for reported heterogeneity comparing individual self-evaluations. Once interpersonal incomparability resulting from the different uses of response scales is removed from the self-assessments, some estimates are reversed in magnitude and signs with respect to the analysis of the collected data., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Public procurement is viewed as a major market force that can be used to promote innovation and drive small and medium-sized enterprises growth. In such cases, procurement system design relies on intermediates that provide vertical linkages between suppliers and providers of innovative services and products. In this work we propose an innovative methodology for decision support in the process of supplier discovery, which precedes the final supplier selection. We focus on data gathered from community-based sources such as Reddit and Wikidata and avoid any use of historical open procurement datasets to identify small and medium sized suppliers of innovative products and services that own very little market shares. We look into a real-world procurement case study from the financial sector focusing on the Financial and Market Data offering and develop an interactive web-based support tool to address certain requirements of the Italian central bank. We demonstrate how a suitable selection of natural language processing models, such as a part-of-speech tagger and a word-embedding model, in combination with a novel named-entity-disambiguation algorithm, can efficiently analyze huge quantity of textual data, increasing the probability of a full coverage of the market.

This paper studies the effect on the spread of Sars-Cov-2 in Italy of schools' re-openings and closures. Exploiting different re-opening dates across regions after the summer break of 2020, I show that early-opening regions experienced more cases in the 40 days following school re-openings compared with late-opening ones. However, there is great uncertainty around the estimates, and this suggests a wide dispersion in the effects of school re-openings on Sars-Cov-2 transmission. I also study the effect of school closures in Campania, one of the biggest regions in Southern Italy. Using a synthetic control approach, I show that school closures are associated with lower numbers of cases relative to the counterfactual group, particularly in younger age groups. In contrast, I find no significant effects on older age groups, which are more likely to require hospitalization. Finally, by exploiting survey data, I provide descriptive evidence on the increased incidence rate among teachers and students relative to the general population, following school re-openings., (Copyright © 2023 Elsevier B.V. All rights reserved.)

We rely on the ESG ratings assigned by four distinct agencies (MSCI, Refinitiv, Robeco, and Sustainalytics) to study the link between ESG scores and firms' cost of debt financing during the Covid-19 pandemic. We document the existence of a statistically and economically significant ESG premium, i.e. better rated companies access debt at a lower cost. Despite some differences across rating agencies, this result is robust to additional controls for the issuer's credit standing as well as several bond and issuer's characteristics. We find that this effect is mainly driven by firms domiciled in advanced economies, whereas creditworthiness considerations prevail for firms in emerging markets. Lastly, we show that the lower cost of capital for highly rated ESG firms is explained both by investors' preference for more sustainable assets and by risk-based considerations unrelated to firms' creditworthiness, such as exposure to climate change risks., (© 2023 Elsevier Inc. All rights reserved.)

The diffusion of COVID-19 and related containment measures practically halted tourism flows, which in many countries generate a significant share of GDP. By leveraging Airbnb data covering the main touristic destinations in Europe, we investigate the impact of the pandemic on the market for short-term rentals up to early 2021. We find that the epidemic reduced dramatically both the supply of apartments available for rents and customers' demand, with travellers cancelling many reservations and reducing new bookings even many months in advance. Accommodations relying relatively more on foreign tourism were the hardest hit and reacted by cutting prices. By exploiting the different timing of the epidemic spread across Europe and the timelines and intensity of the measures adopted to contain it, we show that government mandated restrictions had a stronger impact than the spread of the infection itself. All in all, our results point to a persistent and heterogeneous impact of COVID-19 on the accommodation industry., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Real-world datasets characterized by discrete features are ubiquitous: from categorical surveys to clinical questionnaires, from unweighted networks to DNA sequences. Nevertheless, the most common unsupervised dimensional reduction methods are designed for continuous spaces, and their use for discrete spaces can lead to errors and biases. In this Letter we introduce an algorithm to infer the intrinsic dimension (ID) of datasets embedded in discrete spaces. We demonstrate its accuracy on benchmark datasets, and we apply it to analyze a metagenomic dataset for species fingerprinting, finding a surprisingly small ID, of order 2. This suggests that evolutive pressure acts on a low-dimensional manifold despite the high dimensionality of sequences' space.

This paper analyses the response to the COVID-19 pandemic of inbound tourism to Italy looking at variation across countries and provinces. To this end, it uses weekly data on the number of foreign visitors in Italy from January 2019 until February 2021, as provided by a primary mobile telephony operator. We document a very robust negative relation at the province level between the local epidemic situation and the inflow of foreign travellers. Moreover, provinces with a historically higher share in art-tourism, and those that used to be 'hotel intensive' were hit the most during the pandemic, while provinces with a more prevalent orientation to business tourism proved to be more resilient. Entry restrictions with varying degrees of strictness played a key role in explaining cross-country patterns. After controlling for these restrictions, we observed that the number of travellers that could arrive by private means of transportation decreased proportionally less. Overall, this evidence emphasises that contagion risk considerations played a significant role in shaping international tourism patterns during the pandemic., (© 2022 John Wiley & Sons Ltd.)

We incorporate age-specific socio-economic interactions in a SIR macroeconomic model to study the role of demographic factors for the COVID-19 epidemic evolution, its macroeconomic effects and possible containment measures. We capture the endogenous response of rational individuals who choose to reduce inter- and intra-generational social interactions, consumption- and labor-related personal exposure to the virus, while not internalizing the impact of their actions on others. We find that social distancing measures targeted to the elderly (who face higher mortality risk and are not part of the labor force) are best suited to save lives and mitigate output losses. The optimal economic shutdown generates small gains in terms of lives saved and large output losses, for any given type of social distancing. These results are confirmed by calibrating the model to match real epidemic and economic data in the context of a scenario exercise., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

During the COVID-19 pandemic, several countries have resorted to self-adaptive mechanisms that tailor non-pharmaceutical interventions to local epidemiological and health care indicators. These mechanisms reinforce the mutual influence between containment measures and the evolution of the epidemic. To account for such interplay, we develop an epidemiological model that embeds an algorithm mimicking the self-adaptive policy mechanism effective in Italy between November 2020 and March 2022. This extension is key to tracking the historical evolution of health outcomes and restrictions in Italy. Focusing on the epidemic wave that started in mid-2021 after the diffusion of Delta, we compare the functioning of alternative mechanisms to show how the policy framework may affect the trade-off between health outcomes and the restrictiveness of mitigation measures. Mechanisms based on the reproduction number are generally highly responsive to early signs of a surging wave but entail severe restrictions. The emerging trade-off varies considerably depending on specific conditions (e.g., vaccination coverage), with less-reactive mechanisms (e.g., those based on occupancy rates) becoming more appealing in favorable contexts., Competing Interests: The authors have declared that no competing interests exist.

The COVID-19 pandemic led to a huge surge in deposits, although little is known about how this was distributed. This paper overcomes the lack of timely micro-data on households' liquidity by looking at supervisory data, introducing a new method to estimate the trend in liquidity distribution and the percentage of liquidity-poor households. We find that in 2020 there was a decrease both in the degree of deposit inequality among Italian households and in the share of liquidity-poor households, alongside government support measures that allowed some households at the bottom of the liquidity ladder to save out of their declining income. The increase in households' liquidity improved their ability to repay debts, and this could help spending patterns to rebound once confidence about the economic outlook is restored. Despite this, households with insufficient liquidity buffers still constitute a large share of population, making their debt repayment capacity dependent on the strength of the economic recovery., (© 2022 International Association for Research in Income and Wealth.)

Sickness absence entails large individual and societal costs. Dialogue Meetings (DMs) where the absentee, the employer, and the physician discuss arrangements for full or partial work resumption have been in place in Norway since 2007. In collaboration with the Labour and Welfare Administration, we conducted a large-scale, pre-registered, randomized field experiment to evaluate aspects of the Norwegian DMs policy. We do not find statistically significant effects of summoning to a meeting and we can reject even small threat (notification) effects of sending out letters. We also conduct an extensive search for heterogeneous treatment effects but find no evidence of these., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Real-world data typically contain a large number of features that are often heterogeneous in nature, relevance, and also units of measure. When assessing the similarity between data points, one can build various distance measures using subsets of these features. Finding a small set of features that still retains sufficient information about the dataset is important for the successful application of many statistical learning approaches. We introduce a statistical test that can assess the relative information retained when using 2 different distance measures, and determine if they are equivalent, independent, or if one is more informative than the other. This ranking can in turn be used to identify the most informative distance measure and, therefore, the most informative set of features, out of a pool of candidates. To illustrate the general applicability of our approach, we show that it reproduces the known importance ranking of policy variables for Covid-19 control, and also identifies compact yet informative descriptors for atomic structures. We further provide initial evidence that the information asymmetry measured by the proposed test can be used to infer relationships of causality between the features of a dataset. The method is general and should be applicable to many branches of science., (© The Author(s) 2022. Published by Oxford University Press on behalf of the National Academy of Sciences.)

Strong labor force participation cyclicality during the Covid-19 pandemic has put further into question the capacity of standard Phillips Curve (PC) models to fully capture labor market cyclical conditions. In this paper, we jointly estimate natural unemployment and participation rates (i.e. compatible with constant inflation) through an augmented PC informed by structural labor market flows across employment, unemployment and inactivity. Focusing on Italy we find that, during the pandemic: (i) natural unemployment has remained unchanged, while natural participation has declined slightly, mostly due to a rise in retirement flows driven by a temporary reduction in pension eligibility rules; (ii) virtually all slack was accounted for by the participation margin, which added significant downward pressures to inflation dynamics., (© 2022 Elsevier B.V. All rights reserved.)

We investigate the short-term effects of COVID-19 on labor market flows and how they are mediated by labor market policy. Using Italian administrative data on a sample of active contracts between 2009 and the second quarter of 2020, we show that, before the pandemic, a higher share of female compared to male, young compared to old and low educated compared to high educated workers is employed in non-essential activities. When we look at the change in hirings and separations, from the 9th week of 2020 - the time when first cases and deaths due to COVID-19 were recorded -, we find a pronounced drop in hirings and endings of fixed-term contracts. Layoffs and quits increase after the 9th week, and then decline significantly, reflecting the effects of government intervention. The lifting of the lockdown triggers a slow recovery of labor market flows. Young workers, those on temporary contracts, low-educated workers, those employed in the South and those with no opportunities of working from home experience a greater decline in separation probability, indicating that government policy partly protected them from the labor market impact of the recession. The decline in the separation probability for women is lower than that for men., Supplementary Information: The online version contains supplementary material available at 10.1007/s10888-021-09522-610.1007/s10888-021-09522-6., Competing Interests: Conflict of InterestThe authors declare no conflict of interest., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.)

We investigate whether forward guidance and large scale asset purchases are effective in steering economic expectations in the USA. Using the series of monetary policy shocks recovered in Swanson (J Monet Econ 118:32-53, 2021), local projections, and an algorithm to select the best empirical model, we show that unconventional monetary policies are effective in tilting economic expectations in a direction consistent with central bankers' will. Our empirical findings provide two more insights: responses to LSAP shocks are stronger than those following a FG shock; responses to contractionary LSAP shocks are larger as compared to those stemming from expansionary ones., (© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.)

This paper contributes to the analysis of quantitative indicators (i.e., red flags or screens ) to detect corruption in public procurement. It presents an approach to evaluate corruption risk in public tenders through standardized ML tools applied to detailed data on the content of calls for tenders. The method is applied to roadwork contracts in Italy and three main contributions are reported. First, the study expands the set of commonly discussed indicators in the literature to new ones derived from operative practices of police forces and the judiciary. Second, using novel and unique data on firm-level corruption risk, this study validates the effectiveness of the indicators. Third, it quantifies the increased corruption-prediction ability when indicators that are known to be unavailable to the corruption-monitoring authority are included in the prediction exercise. Regarding the specific red flags, we find a systematic association between high corruption risk and the use of multi-parameter awarding criteria. Furthermore, predictability of the red flag makes them ineffective as prediction tools: the most obvious and scrutinized red flags are either uncorrelated with corruption or, even, negatively associated with it, as it is the case for invoking special procedures due to "urgency," or the extent of publicity of the call for tender., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2022.)

In an attempt to curb the COVID-19 pandemic, several countries have implemented various social restrictions, such as closing schools and asking people to work from home. Nevertheless, after months of strict quarantine, a reopening of society is required. Many countries are planning exit strategies to progressively lift the lockdown without leading to an increase in the number of COVID-19 cases. Identifying exit strategies for a safe reopening of schools and places of work is critical in informing decision-makers on the management of the COVID-19 health crisis. This scoping review describes multiple population-wide strategies, including social distancing, testing, and contact tracing. It highlights how each strategy needs to be based on both the epidemiological situation and contextualize at local circumstances to anticipate the possibility of COVID-19 resurgence. However, the retrieved evidence lacks operational solutions and are mainly based on mathematical models and derived from grey literature. There is a need to report the impact of the implementation of country-tailored strategies and assess their effectiveness through high-quality experimental studies., (© 2020 Elsevier Ltd. All rights reserved.)

Background: Evidence is needed on the effectiveness of wearing face masks in the community to prevent SARS-CoV-2 transmission. Methods: Systematic review and meta-analysis to investigate the efficacy and effectiveness of face mask use in a community setting and to predict the effectiveness of wearing a mask. We searched MEDLINE, EMBASE, SCISEARCH, The Cochrane Library, and pre-prints from inception to 22 April 2020 without restriction by language. We rated the certainty of evidence according to Cochrane and GRADE approach. Findings: Our search identified 35 studies, including three randomized controlled trials (RCTs) (4,017 patients), 10 comparative studies (18,984 patients), 13 predictive models, nine laboratory experimental studies. For reducing infection rates, the estimates of cluster-RCTs were in favor of wearing face masks vs. no mask, but not at statistically significant levels (adjusted OR 0.90, 95% CI 0.78-1.05). Similar findings were reported in observational studies. Mathematical models indicated an important decrease in mortality when the population mask coverage is near-universal, regardless of mask efficacy. In the best-case scenario, when the mask efficacy is at 95%, the R0 can fall to 0.99 from an initial value of 16.90. Levels of mask filtration efficiency were heterogeneous, depending on the materials used (surgical mask: 45-97%). One laboratory study suggested a viral load reduction of 0.25 (95% CI 0.09-0.67) in favor of mask vs. no mask. Interpretation: The findings of this systematic review and meta-analysis support the use of face masks in a community setting. Robust randomized trials on face mask effectiveness are needed to inform evidence-based policies. PROSPERO registration: CRD42020184963., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Coclite, Napoletano, Gianola, del Monaco, D'Angelo, Fauci, Iacorossi, Latina, Torre, Mastroianni, Renzi, Castellini and Iannone.)

In this paper, after a review of the most common financial strategies and products that insurance companies use to hedge catastrophic risks, we study an option pricing model based on processes with jumps where the catastrophic event is captured by a compound Poisson process with negative jumps. Given the importance that catastrophe equity put options (CatEPuts) have in this context, we introduce a pricing approach that provides not only a theoretical contribution whose applicability remains confined to purely numerical examples and experiments, but which can be implemented starting from real data and applied to the evaluation of real CatEPuts. We propose a calibration framework based on historical log-returns, market capitalization and option implied volatilities. The calibrated parameters are then considered to price CatEPuts written on the stock of the main Italian insurance company over the high volatile period from January to April 2020. We show that the ratio between plain-vanilla put options and CatEPuts strictly depends on the shape of the implied volatility smile and it varies over time., (© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021.)

This paper shows that, in a two-country model, where the two economies differ in their level of financial market development, financial integration has sizable short- and medium-term effects, even in the absence of aggregate risks. Consistent with the Lucas paradox, the present work establishes that financial integration can reduce the speed of capital accumulation and increase savings in a developing country still in the process of convergence toward the steady state and with domestic capital market distortions. The level of capital accumulation at the time of integration crucially affects agents' welfare. The closer the economy is to its steady state, the lower are agents' welfare gains in the financially less advanced economy, while they are always negative in the more developed country. Two forces drive these results: precautionary saving and the propensity to move resources from risky capital to safe assets until the risk-adjusted return on capital equalizes the risk-free interest rate. Under the assumption of the constant relative-risk-aversion utility function, those forces are both decreasing in wealth., (© International Atlantic Economic Society 2021.)

We study the role of media reporting of alleged adverse effects of influenza vaccination on adults' (aged 50 or more) decisions to vaccinate against the flu. We exploit the diffusion of news linking suspected deaths to the vaccine, during the 2014 vaccination campaign in Italy. Using daily variation in news items across the 2014 campaign and the previous year campaign, unaffected by media cases, we show that media reporting decreases flu vaccination by about 2.5 % (78 fewer vaccinations per day). The effect, however, is short-lived, as it fades away after approximately 10 days from the news outbreak., Competing Interests: Declaration of Competing Interest The authors report no declarations of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

We analyze the effects of a vaccination program providing free flu vaccine to individuals aged 65 or more on take-up behavior and hospitalization. Using both administrative and survey data, we implement a regression discontinuity design around the threshold at age 65, and find that the effect of the program on take-up ranges between 70% and 90% of the average vaccination rate for individuals aged less than 65. We show that this effect is not entirely driven by an income channel, but also depends on the expected benefits of vaccination. The results on health outcomes provide suggestive evidence that the program reduces the likelihood of emergency hospitalization., Competing Interests: The authors declare that have no relevant or material interests that relate to the research described in this paper., (© 2020 Elsevier B.V. All rights reserved.)

This letter highlights the role of macroeconomic and financial uncertainty in predicting US recessions. In-sample forecasts using probit models indicate that the two variables are the best predictors of recessions at short horizons. Macroeconomic uncertainty has the highest predictive power up to 7 months ahead and becomes the second best predictor - after the yield curve slope - at longer horizons. Using data up to end-2018, out-of-sample forecasts show that uncertainty has significantly contributed to lower the probability of a recession in 2019, which indeed did not occur., Competing Interests: No author associated with this paper has disclosed any potential or pertinent conflicts which may be perceived to have impending conflict with this work. For full disclosure statements refer to https://doi.org/10.1016/j.econlet.2020.109302., (© 2020 Elsevier B.V. All rights reserved.)

The effects of paid parental leave policies on infant health have yet to be established. In this paper we investigate these effects by exploiting the introduction of California Paid Family Leave (PFL), the first program in the U.S. that specifically provides working parents with paid time off for bonding with a newborn. We measure health using the full census of infant hospitalizations in California and a set of control states, and implement a differences-in-differences approach. Our results suggest a decline in infant admissions, which is concentrated among those causes that are potentially affected by closer childcare (and to a lesser extent breastfeeding). Other admissions that are unlikely to be affected by parental leave do not exhibit the same pattern.

Using unique information on a representative sample of US teenagers, we investigate peer effects in adolescent bedtime decisions. We extend the nonlinear least-squares estimator for spatial autoregressive models to estimate network models with network fixed effects and sampled observations on the dependent variable. We show the extent to which neglecting the sampling issue yields misleading inferential results. When accounting for sampling, we find that, besides the individual, family and peer characteristics, the bedtime decisions of peers help to shape one's own bedtime decision.

Understanding the role that drug adherence has on health outcomes in everyday clinical practice is central for the policy maker. This is particularly true when patients suffer from asymptomatic chronic conditions (e.g., hypertension, hypercholesterolaemia, and diabetes). By exploiting a unique longitudinal dataset at patient and physician level in Italy, we show that patients and physicians unobserved characteristics play an important role in determining health status, at least as important as drug adherence. Most importantly, we find that both adherence and prescribed treatment regimen effects are highly heterogeneous across physicians, highlighting their crucial role in shaping patients' health status., (Copyright © 2017 John Wiley & Sons, Ltd.)

The debate on tobacco and fat taxes often treats smoking and eating as independent behaviors. However, the available evidence shows that they are interdependent, which implies that policies against smoking or obesity may have larger scope than expected. To address this issue, we propose a dynamic rational model where eating, smoking, and physical exercise are simultaneous choices that jointly affect body weight and addiction to smoking. Focusing on direct and cross-price effects, we study the impact of tobacco and food taxes, and we show that in both cases a single policy tool can reduce both smoking and body weight. Copyright © 2015 John Wiley & Sons, Ltd., (Copyright © 2015 John Wiley & Sons, Ltd.)