Abstract: This paper uses extended series on income and wealth inequality from the World Inequality Database (WID) covering all world regions over the 1800-2025 period, together with new series on hourly productivity and human capital expenditure, to revisit the relationship between equality and development, with a much broader comparative and historical perspective than previous studies. Over the long-run, we find a strong positive association between equality and productivity. Our proposed interpretation is that the rise of inclusive “social-democratic” institutions (including extended access to human capital, public services and democratic participation) led both to more equality and higher productivity, particularly in Western and Nordic Europe. We discuss the implications for future sustainable development strategies.

Abstract: This paper aims to estimate the existence and the amount of wage compensation arising from the risk of occupational accidents in French industry. For this, it takes data from the 2018 French employment survey to assemble a panel composed 4 quarters of observations for employed individ- uals. With this, an indicator of propensity to accidents at work is estimated by a transformation of the number of days of absence from work assuming a ”sickness” component and an ”accident” component. Starting from the classical Mincerian equation (1958), controls for sex and economic activity (industrial or not) are added to estimate random effects models per individual and positive correlations are found for all except sex, for which it is negative. In the process, the relevance of geographical variables and the type of hiring is discarded. Finally, it is found that occupations declared as risky present a reduction of 4.8% per hour in the French industrial sector and that, therefore, this is not a compensation for the risk assumed by the worker but a penalty.

Abstract: Linking a breath-system disease with the climatic conditions in Mejdoubi, Kyndt & Djennaoui (2020) was clever. The disposal of government's reliable data and the occurrence of the lockdown as a natural “ceteris paribus” was convenient for research purposes. Nevertheless, the authors recognises problems as the limited period of two months during the first wave of the Lockdown in France. This makes it difficult to generalize the findings to other regions or time periods. This short period is added to the lack of control group in this study which makes it difficult to rule out alternative explanations for the observed correlations.This document will focus on correcting the flaws of the paper, rather than in improving it. While most of the problems outlined above require the new data that are beyond the scope of the paper, the accumulative dynamics of contagions can be modeled. 

This is why a two-part methodology is proposed:  In the first, it is proposed to use the Box-Jenkins methodology to model the autocorrelation process of the target variables (deaths and admissions). In the second, I depart from the assumption that the so-called "random part" of the ARIMA model estimation is a combination of a stochastic process and the omitted variables. Accepting this, it would be correct to expect a significant correlation of the residuals of the ARIMA with the climatic variables. This is why it is proposed to incorporate the authors’s proposed lags (8 days for admissions and 15 for deaths)to the an ARIMAX model for asseging their significance as well as to run an Cross Correlation test for identifying higher correlationships of the residuals with the climatic variable lags for proposing new conclusions.