Juan C. Palomino

Bio: Juan C. Palomino is an academic researcher from University of Oxford. The author has contributed to research in topics: Gini coefficient & Socioeconomic status. The author has an hindex of 4, co-authored 10 publications receiving 104 citations.

Channels of Inequality of Opportunity: The Role of Education and Occupation in Europe

Abstract: Inequality of Opportunity (IO) refers to that inequality stemming from factors, called circumstances, beyond the scope of individual responsibility, such as gender, race, place of birth or socioeconomic background. In general, circumstances do not directly convert into future individual’s income. Indeed, different circumstances in childhood lead to different levels of education and different occupational categories which, in turn, contribute to generate divergent levels of income during adulthood. Using the Intergenerational Transmission modules in 2005 and 2011 from the EU-SILC, we estimate the importance of attained education and occupational category as mediating channels in the generation of IO in 26 European countries. We find that the attained level of education channels up to 30% of total IO, with important differences across Europe. Once attained education is taken into account, occupation explains less than 5% of IO in most countries. Moreover, the importance of education as a channel for IO is negatively correlated both with the share of the population that attains tertiary levels of education and with the importance of government expenditure in education relative to GDP.

Peru's Regional Growth and Convergence in 1979-2017: An Empirical Spatial Panel Data Analysis

Abstract: This paper analyzes the process of spatial convergence of growth in Peru’s 24 regions over 1979-2017. We perform an exploratory analysis of spatial data with global and local statistics, such as Moran I, to provide empirical evidence of spatial dependencies in regional per capita GDP. We then estimate the convergence equation using spatial panel models that control for spatial heterogeneity and spatial interdependence, as well as other structural economic features at the regional level. The empirical results show that spatial convergence is a very reliable conclusion over this period, and prove that spatial regional per capita GDP spillovers play an essential role in determining growth at the local level. Furthermore, the Spatial Durbin model is preferred in the formation of four clusters of convergence. The first cluster is highly productive and dynamic; the second cluster is composed by Jungle and negative-productivity regions; the third cluster is formed by moderately productive and Coast regions; and the fourth cluster is composed by stagnating and Highland regions. Finally, these results may be instrumental in giving greater focus to long-run government policies targeting stagnant and poor regions. JEL Classification-JEL: C21, C23, R11 Keywords: Convergencia Regional; Regional Spillovers; Dependencia Espacial; Modelos Espaciales de Datos de Panel; Clubes de Convergencia

Wealth inequality, intergenerational transfers and socioeconomic background

Abstract: This paper estimates the contribution of intergenerational transfers (inheritances and gifts) and socioeconomic background to wealth inequality in four OECD countries: France, Spain, Great Britain and the United States. We generate a non-parametric counterfactual distribution where all differences in wealth associated with the intergenerational transfers received and the socioeconomic background have been removed. Despite the diversity of the four countries analysed, we find similar patterns in the results. The combined contribution of intergenerational transfers and socioeconomic background to wealth inequality is sizeable in all four countries studied, ranging from 37% in Great Britain to 48% in the US. When interactions between the two factors are controlled for, the net contribution of inheritances and gifts is between 23% and 30%, while the net contribution of family background lies between 4% and 11%. These values are substantial and reveal that the importance of intergenerational transfers in all these countries is at least twice that of socioeconomic background.

Wage Inequality and Poverty Effects of Lockdown and Social Distancing in Europe

Abstract: Social distancing and lockdown measures taken to contain the spread of COVID-19 may have distributional economic costs beyond the contraction of GDP. Here we evaluate the capacity of individuals to work under a lockdown based on a Lockdown Working Ability index which considers their teleworking capacity and whether their occupation is essential or closed. Our analysis reveals substantial and uneven potential wage losses across the distribution all around Europe and we consistently find that both poverty and wage inequality rise in all European countries. Under four different scenarios (2 months of lockdown and 2 months of lockdown plus 6 months of partial functioning of closed occupations at 80%, 70% and 60% of full capacity) we estimate for 29 European countries an average increase in the headcount poverty index that goes from 4.9 to 9.4 percentage points and a mean loss rate for poor workers between 10% and 16.2%. The average increase in the Gini coefficient ranges between 3.5% to 7.3% depending on the scenario considered. Decomposing overall wage inequality in Europe, we find that lockdown and social distance measures produce a double process of divergence: both inequality within and between countries increase.

Employment impact of Covid-19 crisis: from short term effects to long terms prospects

Abstract: We contribute to the assessment of the employment implications of the COVID crisis by classifying economic sectors according to the confinement decrees of three European countries (Germany, Spain and Italy). The analysis of these decrees can be used to make a first assessment of the implications of the COVID crisis on labour markets, and also to speculate on mid and long-term developments, since the most and least affected sectors are probably going to continue to operate differently until a vaccine or other long-term solution is found. Using an ad-hoc extraction of EU-LFS data, we apply this classification to the analysis of employment in Germany, Italy and Spain but also UK, Poland and Sweden, in order to cover the whole spectrum of institutional labour market settings within Europe. Our results, in line with recent literature, show that the employment impact is asymmetric within and between countries. In particular, the countries that are being hardest hit by the pandemic itself (Spain and Italy, and also the UK) are the countries more likely to suffer the worst employment implications of the confinement, because of their productive specialisation and labour market institutions. Indeed, these were also the labour markets that were more vulnerable before the crisis: characterised by high unemployment and precarious work (especially temporary contracts).

Estimation of differential occupational risk of COVID-19 by comparing risk factors with case data by occupational group.

Abstract: Background The disease burden of coronavirus disease 2019 (COVID-19) is not uniform across occupations. Although healthcare workers are well-known to be at increased risk, data for other occupations are lacking. In lieu of this, models have been used to forecast occupational risk using various predictors, but no model heretofore has used data from actual case numbers. This study assesses the differential risk of COVID-19 by occupation using predictors from the Occupational Information Network (O*NET) database and correlating them with case counts published by the Washington State Department of Health to identify workers in individual occupations at highest risk of COVID-19 infection. Methods The O*NET database was screened for potential predictors of differential COVID-19 risk by occupation. Case counts delineated by occupational group were obtained from public sources. Prevalence by occupation was estimated and correlated with O*NET data to build a regression model to predict individual occupations at greatest risk. Results Two variables correlate with case prevalence: disease exposure (r = 0.66; p = 0.001) and physical proximity (r = 0.64; p = 0.002), and predict 47.5% of prevalence variance (p = 0.003) on multiple linear regression analysis. The highest risk occupations are in healthcare, particularly dental, but many nonhealthcare occupations are also vulnerable. Conclusions Models can be used to identify workers vulnerable to COVID-19, but predictions are tempered by methodological limitations. Comprehensive data across many states must be collected to adequately guide implementation of occupation-specific interventions in the battle against COVID-19.

Modern Infectious Diseases: Macroeconomic Impacts and Policy Responses

Abstract: We discuss and review literature on the macroeconomic effects of epidemics and pandemics since the late 20th century. First, we cover the role of health in driving economic growth and well-being and discuss standard frameworks for assessing the economic burden of infectious diseases. Second, we sketch a general theoretical framework to evaluate the tradeoffs policymakers must consider when addressing infectious diseases and their macroeconomic repercussions. In so doing, we emphasize the dependence of economic consequences on (i) disease characteristics; (ii) inequalities among individuals in terms of susceptibility, preferences, and income; and (iii) cross-country heterogeneities in terms of their institutional and macroeconomic environments. Third, we study pharmaceutical and nonpharmaceutical policies aimed at mitigating and preventing infectious diseases and their macroeconomic repercussions. Fourth, we discuss the health toll and economic impacts of five infectious diseases: HIV/AIDS, malaria, tuberculosis, influenza, and COVID-19. Although major epidemics and pandemics can take an enormous human toll and impose a staggering economic burden, early and targeted health and economic policy interventions can often mitigate both to a substantial degree.

Tourism and Sustainability in Times of COVID-19: The Case of Spain.

Abstract: The aim of this paper is to study the effects of the spread of the COVID-19 virus in different regions and its impact on the economy and regional tourist flows. To this end, the researchers have been guided by a set of propositions which they have tried to demonstrate with the results obtained. This research shows that the impact of the pandemic is still being evaluated. The analysis of the relationship between the tourism sector and the pandemic outbreak in Spain provides an instructive case study to assist tourism in its recovery process. The paper delves into the impacts on the main Spanish touristic regions during the pandemic and providing implications for tourism recovery. In Spain, the tourism sector is of major economic importance, becoming one of the most vulnerable countries when crisis affects this industry. The negative image of the country due to the high infection rates has had a negative impact on travel and tourism. The Balearic Islands have been the most affected region with an 87% decrease in tourist visitors. The trips made by Spanish residents inside the Spanish territory shows the first increase found in the series analyzed. Domestic tourism not only represents an opportunity for all regions in this critical situation, but the types of accommodation also play a key role.