In this paper, a comparison has been made between the average crash rate, cost overruns and time overruns of the road sections concessioned with the estimated level that these sections would have if they had not been concessioned for the Peruvian case. For this exercise, the Propensity Score Matching methodology has been used that guarantees correct comparability between the concessioned and non-concessioned highways. This technique matches the unique characteristics that distinguish the control (to try to make them more similar) and treatment groups. The main result is that the crash rate, number of injuries, number of deaths, cost overruns and time overruns are lower in the concessioned sections than in the non-concessioned sections. In addition to this, the cost of crashes on concessioned and non-concessioned highways for Peru has also been estimated. In this case, the average annual cost per crash on the concessioned highways in the period 2015–2019 would be USD 65.72 million, while for the non-concessioned highways it would be USD 254 million. In other words, if all highways were concessioned, Peru would save an average of US $ 189 million per year from traffic crashes.
We carry out a randomized controlled trial to evaluate the effect of three types of messages sent to taxpayers on their compliance with the rental income tax (direct effect) and the spillovers produced on the capital gains and the self-employment income taxes (indirect effects). One message highlights detection, other appeals to social norms, and the third appeals to altruism. We also perform a 15-month follow-up to determine if the treatment increases tax revenues in a sustained manner. We find that the message addressing detection produces a positive and sustained direct effect and a negative spillover on the other two taxes. The “social norms” message has no direct effect but produces a sustained negative spillover on the capital gains tax. The message appealing to altruism produces a transitory negative effect and no statistically significant spillovers. We show there is substantial risk of overestimating the tax revenues produced by the messages if one relies only on their direct effects.
Using a difference‐in‐difference approach, we test the causal link between environmental disasters and mental health indicators in rural areas of Peru by exploiting the spatial variation in exogenous oil spills and the differences in their timing for the period 2014 to 2018. We find that, after controlling for time‐varying controls and year fixed effects, oil spills lead to a significantly higher probability of suffering psychological distress. We also explore likely mechanisms that explain this causal impact. Finally, we present an event study and apply robustness tests that further support our findings.
Resumen Introducción La pandemia producida por el SARS-CoV-2 ha impactado en los sistemas educativos, lo cual justifica la necesidad de investigar acerca de las capacidades emocionales de los estudiantes universitarios para enfrentar los desafíos que la COVID-19 impone. Objetivo Analizar las evidencias de validez y confiabilidad de la Wong-Law Emotional Intelligence Scale (WLEIS) en estudiantes cubanos de Estomatología. Materiales y métodos Estudio transversal con diseño instrumental. La escala fue administrada mediante un cuestionario virtual y posteriormente distribuida a través de las redes sociales a 307 estudiantes (81 varones y 226 mujeres). Se realizó un análisis factorial confirmatorio y se evaluaron la consistencia interna y la relación de la escala con otras variables. Resultados Mediante el análisis factorial confirmatorio se evaluó el modelo de cuatro factores correlacionados y se encontró un ajuste adecuado, χ²(98) = 303,1, p < 0,001, CFI = 0,948, TLI = 0,937, RMSEA = 0,083 y SRMR = 0,064. Los resultados de las consistencias internas omega son de ωSEA = 0,84, ωOEA = 0,77, ωUOE = 0,83 y ωUROE = 0,91. Con respecto a la relación del WLEIS con otras variables, se tienen correlaciones entre 0,22 y 0,51 con bienestar general y correlaciones inversas entre −1 y −0,29 de tres de sus dimensiones con depresión, presentando así evidencias de validez convergente y discriminante. Conclusión La WLEIS en estudiantes cubanos de Estomatología en tiempos de COVID-19 resultó ser válida y confiable.
Objective To evaluate the relationship between job satisfaction, burnout syndrome (BS) and depressive symptoms (DS) based on the job demand–control framework model on a nationally representative sample of physicians working in the Peruvian Health System. Setting We carried out a secondary data analysis of the National Survey of Satisfaction of Users in Health 2016 in Peru. Primary and secondary outcome measures Our study assessed the development of the predictive model and had two parts: (1) to evaluate the association among the variables based on the job demand–control framework, and (2) to assess the proposed model acceptability using the structural equation modelling approach to estimate goodness-of-fit indices (GOFIs). Participants We excluded physicians older than 65 years, who did not report income levels or who had missing data related to the workplace. Thus, we analysed 2100 participants. Results The prevalence of DS was 3.3%. Physicians’ work-related illnesses had more probability to result in DS (prevalence ratio=2.23). DS was moderately related to BS dimensions (r>0.50); nevertheless, the relationships between DS and the three job satisfaction scales were weak (r<0.30). The first predictive model based on the variables, DS, BS and job satisfaction, had low GOFIs (comparative fit index (CFI)=0.883; root mean square error of approximation (RMSEA)=0.125). In a second evaluation, we used models with correlated errors obtaining optimal GOFIs (CFI=0.974; RMSEA=0.060). Conclusions Our study identified a stable model to explain the relationship between job satisfaction, BS and DS among physicians. The results are consistent with the job demand–control framework. They could be applied to decision-making in occupational contexts in Latin American low/middle-income countries.
Does automation adoption mitigate the COVID-19 infection rate of employees? What resources and internal and external factors need to be configured with automation to mitigate COVID-19 contagion from employees successfully? According to the type of automation. What resources efficiently complement to mitigate the contagion rate from employers? From a fuzzy-set qualitative comparative analysis (fsQCA) approach, we analyzed 759 manufacturing firms in Finland, drawn from the World Bank 2020 Enterprise Survey; this study addresses the multiple configurations that drive pandemic risk mitigation and management. We find that configurations under automation reduce the risk of employee infection. Our results show the critical role of automation in employee safety. We argue that access to government support and the development of technological innovation are necessary conditions for implementing measures to prevent and mitigate the risk of contagion in the employee. In addition, the first configuration states that manufacturing firms employing soft automation can successfully mitigate employee exposure. The second configuration states that high human resource flexibility successfully complements firms with complex automation to achieve high mitigation. Finally, the third configuration shows those manufacturing firms that employ low-tech automation (manual processes); in this manner, digitization enables successfully mitigating pandemic contagion. Moreover, it suggests recommendations for policymakers and managers.
Strengthening linkages with markets along the value chain is a promising pathway to increase agricultural productivity, welfare, and food security of smallholder producers in developing countries. Our study investigates the impact of an integrated value chain project, which linked producer organizations to markets and provided various types of training to their members. Using primary survey data from Nepal, we apply propensity score matching to ensure common support and statistical balance between project (treatment) and non-project (control) households. We implement the selectivity-corrected stochastic production frontier methodology to control for unobservable characteristics and estimate a simulation-based stochastic metafrontier to account for different technological levels between the two groups of households. Comparing results between the translog and Cobb-Douglas production frontiers, we find that the more flexible translog specification shows no signs of selectivity bias while this bias is present with the Cobb-Douglas, motivating the need to correct for selectivity. Our main results from the metafrontier analysis indicate that project impacts are reflected in substantial technological gaps and significant meta-technical efficiency differences in favor of treatment households. Thus, this study shows that strengthening linkages between producers and markets can have a large positive effect on productivity. Heterogeneity analysis suggests that more vulnerable producers, including those with fewer years of education and smaller farms, receive relatively higher returns from the project compared to their counterparts.
Due to the emotional impact of COVID-19 on university students, the goal was to explore the relationship between anxiety, depression, psychological well-being, and life satisfaction among pre-professional interns. The research was carried out using an explanatory cross-sectional design, with the participation of 1011 pre-professional interns of 13 health networks from the department of Puno (Peru). Data were collected using the Satisfaction with Life Scale, Generalized Anxiety Disorder Scale-2, Patient Health Questionnaire 2, and the Psychological Wellbeing Scale. The main data analysis was carried out using the R statistical software, and implementing the confirmatory factor analysis technique, which evidenced that the explanatory model provides an acceptable value. Based on the above, a negative relationship between depression and life satisfaction, (β = -.60, p < .001) and a positive relationship between anxiety and life satisfaction (β = .28, p < .001) was shown, in addition to a mediating effect of the psychological wellbeing related to depression and life satisfaction (p < .001). In conclusion, life satisfaction is explained concerning the degree of depression and anxiety, as well as the moderating effect of psychological well-being. Despite that, there is an urgent need to take preventive actions to strengthen the mental health of the pre-professional health interns, who have also been providing support during the COVID-19 pandemic.
Migration is not an event, but an interactive process whereby individuals on the move make decisions in their social and political contexts. As such, one expects migrant mental health to change over time. To examine this relationship, we conducted a meta-analysis, the first to our knowledge, to identify the impact of migration phase and migration type on the prevalence of mental health in migrant populations. We searched PubMed, PsycInfo, and Embase for studies published between January 1, 2010, and January 1, 2020 (Prospero ID: 192751). We included studies with international migrants reporting prevalence rates for post-traumatic stress disorder (PTSD), depression, and/or anxiety. The authors extracted data from eligible studies and tabulated mental health prevalence rates, relevant migration condition (e.g., migration type or phase), and methods (e.g., sample size). Full text review resulted in n = 269 manuscripts included in the meta-analysis examining PTSD (n = 149), depression (n = 218), and anxiety (n = 104). Overall prevalence was estimated for PTSD (30.54 %, I² = 98.94 %, Q = 10,443.6), depression (28.57 %, I² = 99.17 %, Q = 13,844.34), and anxiety (25.30 %, I² = 99.2 %, Q = 10,416.20). We also estimated the effect of methodological and migration factors on prevalence in PTSD, depression, and anxiety. Our findings reveal increased prevalence of mental health due to forced migration and being in the journey phase of migration, even when accounting for the influence of methods.
Quinoa is a traditional food grain that originated in the Peruvian Andean region. The United Nations declared 2013 to be the International Year of Quinoa (iyq). This official launch had a great impact around the world. On the contrary, it had minor impact on the consumption of quinoa in Peru, which remained relatively steady in the following years. However, the covid-19 pandemic raised concerns about nutrition and health among consumers. Therefore, this study seeks to analyze quinoa consumption in Peru during the covid-19 pandemic. Primary data were collected between September 2020 and August 2021 in Lima Metropolitan Area, Peru. Exploratory factor analysis with varimax rotation was performed for data analysis, and logistic binomial analysis was then conducted to consolidate the hypothesis of this study. The main outcomes identified were that (i) current quinoa consumers in Peru ate quinoa even before the iyq; (ii) consumers who are concerned about their health and nutrition needs increased quinoa consumption during the pandemic; (iii) women showed a higher probability of daily to weekly trend in quinoa consumption; and (iv) people with the highest income have more probability of purchasing food at supermarkets than those who earn less. The findings of this study can shed some light on consumers’ expectations and perceptions regarding quinoa consumption behavior during covid-19.
This article presents the characteristics that the Catholic hierarchy has displayed over the course of a century in the political arena, as well as the importance that religious elements have exercised over the legitimacy of some parties and governments in Peru. It specifically analyzes the clergy and their relation with the State, as well as interpreting how they understood their participation and influence in local politics. In addition, parties and regimes over the course of a century are analyzed, emphasizing the presidential election campaigns of 1990 and 2021, in order to discuss the limits that political organizations have experienced in monopolizing religious representations. This study will help to better understand the nature of Catholicism in Latin American politics.
The International Year of Quinoa (IYQ) (2013) showcased quinoa to the world and generated a rapid expansion in international demand for quinoa. It also increased the level of consumption in Peru. Peruvian ethnic identity reflects the food culture of origin. This research aims to determine the relationship between ethnic identity and other Theory of Planned Behavior factors on quinoa consumption intention and frequency of consumers in Top Lima and Modern Metropolitan Lima, Peru. A survey of 381 respondents was conducted between April and September 2017, and structural equation modeling was used to analyze the data. Contrary to expectations, intention and frequency of consumption of quinoa were negatively affected by “ethnic identity” (p < 0.05). This result is related to the promotion by the IYQ and Marca Perú (brand name Peru) and the gastronomic boom.
Background To understand the impact of the COVID-19 pandemic on mortality, this study investigates overall, sex- and age-specific excess all-cause mortality in 20 countries, during 2020. Methods Total, sex- and age-specific weekly all-cause mortality for 2015–2020 was collected from national vital statistics databases. Excess mortality for 2020 was calculated by comparing weekly 2020 observed mortality against expected mortality, estimated from historical data (2015–2019) accounting for seasonality, long- and short-term trends. Crude and age-standardized rates were analysed for total and sex-specific mortality. Results Austria, Brazil, Cyprus, England and Wales, France, Georgia, Israel, Italy, Northern Ireland, Peru, Scotland, Slovenia, Sweden, and the USA displayed substantial excess age-standardized mortality of varying duration during 2020, while Australia, Denmark, Estonia, Mauritius, Norway, and Ukraine did not. In sex-specific analyses, excess mortality was higher in males than females, except for Slovenia (higher in females) and Cyprus (similar in both sexes). Lastly, for most countries substantial excess mortality was only detectable (Austria, Cyprus, Israel, and Slovenia) or was higher (Brazil, England and Wales, France, Georgia, Italy, Northern Ireland, Sweden, Peru and the USA) in the oldest age group investigated. Peru demonstrated substantial excess mortality even in the <45 age group. Conclusions This study highlights that excess all-cause mortality during 2020 is context dependent, with specific countries, sex- and age-groups being most affected. As the pandemic continues, tracking excess mortality is important to accurately estimate the true toll of COVID-19, while at the same time investigating the effects of changing contexts, different variants, testing, quarantine, and vaccination strategies.
We study how the Chilean population’s well-being responded to the strategy implemented by their health authorities, known as Dynamic Quarantine , to contain the spread of coronavirus in which municipalities periodically entered and exited lockdowns. This unique scheme, together with the population’s socioeconomic heterogeneity, facilitates the estimation of changes in this well-being as differentiated by socioeconomic status. Using Google Trends to compute measures of well-being, we find strong evidence that socioeconomic status induces heterogeneity in these changes; thus, neglecting this heterogeneity may lead to misleading prescriptions for the public policy that addresses the psychological effects of lockdowns.
Objective To examine the effect of family and academic satisfaction on the self-esteem and life satisfaction among Peruvian university students. Method Of the 1,182 Peruvian university students who participated, 364 were male; and 818 were female; and ranged from 17 to 39 years of age (mean = 20.67, SD = 4.4). The family satisfaction scale (FSS), the Escala breve de satisfacción con los estudios (EBSE; Brief Academic Satisfaction Scale in Spanish), Rosenberg’s self-esteem scale (RSES), and the satisfaction with life scale (SWLS) were used to perform the assessments. Results The study model showed an adequate fit (χ ² 19.5, p < 0.001, CFI = 0.977, RMSEA = 0.057), confirming the association between family satisfaction and life satisfaction (β = 0.26, p < 0.001) and self-esteem (β = 0.35, p < 0.001), and the correlation between academic satisfaction and self-esteem (β = 0.35, p < 0.001) and life satisfaction (β = 0.23, p < 0.001). The model accounted for 42% of life satisfaction. Conclusion Family satisfaction and academic satisfaction affect self-esteem and life satisfaction.
This study analyzes secondary data for a sample of 4,606 consumers from 10 countries to measure their political consumerism (having boycotted or buycotted a product or brand in the last year). It also determines the profile of the international political consumer. The non-parametric CART (Classification and Regression Trees) technique is used for the analysis. The results identify the consumer’s country of residence as the most influential variable on political consumerism, followed by consumers’ environmental concerns and level of education. Given the complexity of the country construct, future studies should analyze specific aspects related to the social context of each country.
In the Americas, the Inter-American Commission on Human Rights (IACHR) and the Inter-American Court of Human Rights (IACtHR) have established that the principle of equality and non-discrimination requires States to both ensure that migrants are not discriminated against on any of the protected grounds of the American Convention on Human Rights, as well as to take specific action to protect certain groups of migrants that are in a situation of vulnerability. Via a comparative quantitative analysis of the immigration and refugee laws, as well as implementing regulations, of 20 Latin American countries, we examine the extent of non-discrimination and special protection provided by the region’s migratory legislation. Our results reveal three main findings. First, more recent immigration and refugee laws tend to be more expansive, which reflects the period of migratory liberalisation in the region. Second, while non-discrimination clauses are more dominant in laws, special protection clauses are primarily present in implementing regulations. This suggests that countries see special protection as a tool to positive discrimination of particularly vulnerable groups. Third, although we identify an overall expansion on protection grounds, countries’ migratory laws mostly reflect traditional categories like: sex/gender; race/ethnicity/colour; nationality; economic/social condition; and religion. Overall, although laudable, the impact of these provisions on reversing structural discrimination from an intersectional approach remains questionable.
Partial currency substitution typically occurs in small open economies amid economic crises. Often, the foreign currency continues to circulate even after macroeconomic stability returns. Central banks have responded by applying de-dollarization policies. We extend the model in Matsuyama et al. (1993) and implement an experiment to study the effectiveness of two policy instruments: (1) taxes on domestic transactions in foreign currency and (2) a reduction in the storage cost of local currency. We contribute to the theoretical literature by characterizing a new circulation regime for small open economies where agents use the foreign currency solely for international trade and settle domestic transactions exclusively in local currency. Our experimental evidence suggests that both taxes and storage cost reductions can foster de-dollarization as they reduce foreign currency acceptance and reinforce the use of local currency. However, we find that the impact of a reduction in the storage costs of the local currency is more significant and robust. It lowered the acceptance rate of foreign currency by more than 20 percentage points and increased the acceptance of local currency by more than 30 percentage points. On the other hand, the tax policy reduced foreign currency acceptance by a smaller amount and only for encounters with foreign agents.
This paper studies demand for public loading zones in urban environments and seeks to develop a machine learning algorithm to predict their demand. Understanding and predicting demand for public loading zones can: (i) support better management of the loading zones and (ii) provide better pre-advice so that transport operators can plan their routes in an optimal way. The methods used are linear regression analysis and neural networks. Six months of parking data from the city of Vic in Spain are used to calibrate and test the models, where the parking data is transformed into a time-series format with forecasting targets. For each loading zone, a different model is calibrated to test which model has the best performance for the loading zone’s particular demand pattern. To evaluate each model’s performance, both root mean square error and mean absolute error are computed. The results show that, for different loading zone demand patterns, different models are better suited. As the prediction horizon increases, predicting further into the future, the neural network approaches start to give better predictions than linear models.
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