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This article analyzes the relative level and evolution of the net nutritional status of manufacturing workers and craftsmen born in the last third of the eighteenth century in central Spain. It uses the anthropometric and occupational data included in the records of the general conscription carried out during the Napoleonic invasion. The findings are interpreted in light of the recent contributions made regarding the evolution of the economy and industrial products of central Spain during the second half of the eighteenth century. Significant differences can be observed between the different professions and economic sectors, largely explained by income levels, a possible selection for some occupations in accordance with physical characteristics, and access to animal proteins. Furthermore, the data also reveal an overall decrease in height and an increase in inequality between professions during the period.

In this paper we investigate the sensitivity of stochastic population forecasts produced by means of the Scaled Model of Error with respect to the choice of the correlation parameters. In particular, we evaluate the impact that a change in the specification of the correlation of the age-specific fertility forecast error increments across time and age and of the correlation of the age-specific mortality forecast error increments across time, age and sex has on the forecasts of the Total Fertility Rate and of the Male and Female Life Expectancies respectively. In our opinion a sensitivity analysis of this kind is extremely useful, since up to now the relevance and the impact of the choice of the Scaled Model of Error input parameters has not be discussed in detail. Such analysis will provide users with a better understanding of the model itself.

Propensity Score Matching (PSM) has become a popular approach to estimation of causal effects. It relies on the assumption that selection into a treatment can be explained purely in terms of observable characteristics (the unconfoundedness assumption) and on the property that balancing on the propensity score is equivalent to balancing on the observed covariates. Several applications in social sciences are characterized by a hierarchical structure of data: units at the first level (e.g., individuals) clustered into groups (e.g., provinces). In this paper we explore the use of multilevel models for the estimation of the propensity score for such hierarchical data when one or more relevant cluster-level variables is unobserved. We compare this approach with alternative ones, like a single level model with cluster dummies. By using Monte Carlo evidence we show that multilevel specifications usually achieve reasonably good balancing in cluster level unobserved covariates and consequently reduce the omitted variable bias. This is also the case for the dummy model.

In the last few years, the UK has adopted a fiercely competitive business tax policy by reducing the general tax burden on business and expanding individual regimes targeted to mobile factors: CFC rules, interest deductibility rules, and the Patent Box have made the UK very attractive for internationally mobile capital and profits. As the same time, the UK has strongly supported the OECD BEPS project aimed at reducing multinationals’ tax avoidance and, hence, we argue, at eliminating or constraining forms of tax competition among countries based on individual regimes targeted to mobile capital and profits. We claim that, especially in the implementation phase of the BEPS recommendations, there will be tensions between the UK competitiveness agenda and its support for the BEPS. Such tensions will be reconciled by shifting the UK tax competition policy from a mix of rate-based plus individual regimes policy to more of a rate-based approach. In this scenario, the government will have to tighten some specific measures aimed at attracting highly mobile capital and profits, such as the patent box regime and possibly interest deductions. At the same time, it will reduce the tax burden on both mobile and less mobile activities by implementing economy-wide cuts, allowed under BEPS. Most likely, such cuts would come from a further reduction in the headline corporate tax rate and the cuts announced in the July 2015 Budget should be interpreted in this light. Cuts in the headline rate essentially reduce the taxation on profits but they do not take account of the fact that for other decisions such as investment in tangible assets and information and communications technology, other elements of the tax code, such as capital allowances, are more important. To foster real investment, the government could consider an increase in capital allowances. Another option would be the introduction of an Allowance for Corporate Equity (ACE). The interesting feature of the ACE in the context of BEPS is that it reduces the incentive to classify financing instruments as tax-advantaged debt.

Interpersonal trust favors the expansion of organizations by allowing the delegation of decisions and tasks among anonymous others or people that interact only infrequently. We document these facts for a representative survey of Italian manufacturing firms and use this source of data to construct an industry-specific measure of need-for-delegation in production. We then show that trust shapes comparative advantage, as high-trust regions and countries exhibit larger value added and export shares in delegation-intensive industries relative to other industries. Such effects are associated with an increase in average firm size, while the number of firms is not significantly affected. Larger average size reflects in turn a shift of the distribution away from the smallest firms, consistently with the idea that trust allows organizations to expand beyond the narrow circle of family members and close friends.

As more studies focus on social trust and link it to the working of economies and societies, measuring properly this concept is growing in importance. Indeed, as it is a complex construct, entangled to other notions such as reciprocity, it is hard to obtain reliable and accurate measures of it. To mend for this, the OECD has launched Trustlab: a project aimed at creating the first internationally comparable and nationally representative database on trust and social preferences using both survey and experimental approaches. As of March 2018, Trustlab surveys have been run in 6 countries. In this paper we present the data and peculiarities of Trustlab Italy, in which, in addition to the measures of trust, data on personality traits and fertility intentions have been collected.

The vast majority of studies looking into the relationship between childbearing and subjective well-being uses overall measures where respondents either report their general level of happiness or their life satisfaction, leaving substantial doubt about the underlying mechanisms. However, life satisfaction and happiness are intuitively multidimensional concepts, simply because there cannot be only one aspect that affects individuals' well-being. In this study, by considering seventeen specific life satisfaction domains, these features come out very clearly. Whereas all the domains considered matter for the overall life satisfaction, only three of them, namely satisfaction with leisure, health and satisfaction with the partnership, change dramatically surrounding childbearing events. Even though we cannot generalize (since these results stems from one particular panel survey, i.e. Household Income and Labour Dynamics in Australia data), it appears that the typical anticipation and post-child decrease of life satisfaction, so often found in existing studies, stem from changes in these three domains.

Good estimates of HIV prevalence are important for policy makers in order to plan control programs and interventions. Although population-based surveys are now considered the "gold standard" to monitor the HIV epidemic, they are usually plagued by problems of nonignorable nonresponse. This paper uses the partial identification approach to assess the uncertainty caused by missing HIV status. We show how to exploit the availability of panel data and the absorbing nature of HIV infection to narrow the worst-case bounds without imposing assumptions on the missing-data mechanism. Applied to longitudinal data from rural Malawi, the Malawi Diffusion and Ideational Change Project (MDICP), our approach results in a reduction of the width of the worst-case bounds by about 18.2 percentage points in 2004, 13.2 percentage points in 2006, and 2.4 percentage points in 2008. We also use plausible instrumental variable and monotone instrumental variable restrictions to further narrow the bounds.

Studies adopting the Theory of Planned Behavior (TPB) mostly use quantitative methods. Sometimes, however, researchers choose to use a qualitative method because of the nature of available data (e.g., interviews) or availability of only a limited number of cases. This paper describes a study in which the TPB was used with qualitative methods to explain differences in university teaching. It focuses primarily on the methods used: qualitative data coding, data analysis and interpretation, and methods for presenting and supporting results. The study explored factors which influence university teachers to adopt teaching models based on online social interaction when an e-learning platform is used to complement undergraduate classroom teaching. Participants were 26 university teachers (15 from Australia and 11 from Italy). They responded to a semi-structured interview based on the TPB. Three approaches to use of e-learning platforms were identified: upload of materials, use of discussion forums, and computer-supported collaborative learning (CSCL). Using this approach, it was possible to highlight substantial differences in the attitudes, social influence, and perceived behavioral control among the three groups.

In the past decade, the world has witnessed increased climate change impacts with many countries experiencing more frequent and more severe climate extremes. With public support being fundamental in scaling up climate action, here, we analyze the impact of exposure to climate extremes on environmental concern and Green voting for a large panel of European countries. Combining high-resolution climatological data with regionally aggregated and harmonized information on environmental concern (42 Eurobarometer surveys, 2002-2019, 34 countries) and European Parliamentary electoral outcomes (7 elections, 1990-2019, 28 countries) at the subnational level, we find a significant and sizeable effect of temperature anomalies, heat episodes and dry spells in the previous 12 months on green concern and voting. The effects differ significantly by region and are most pronounced in regions with a cooler Continental or temperate Atlantic climate, and weaker in regions with a warmer Mediterranean climate. The relationship is moderated by regional GDP suggesting that climate change experience increase public support for climate action only under favorable economic conditions. By empirically documenting the important role of contextual influences and regional differences on green concern and voting, our findings have important implications for the current efforts to promote and implement climate actions in line with the Paris Agreement.