Changing selection into full-time work and its effect on wage inequality in Germany

To explore whether changes in the selection into full-time work among German men were a driver in the rise in wage inequality since the mid-1990s, we propose a modification of selection-corrected quantile regressions. Addressing Huber and Melly’s (J Appl Econom 30(7):1144–1168, 2015) concerns, this modification allows us to estimate the effects of selection with respect to both observables and unobservables. Our findings show that those employed in 1995 would have had lower wages in 2010 than those employed in 2010 and wage dispersion would have been higher, suggesting that full-time workers have become less heterogeneous over time.

Implementing quantile selection models in Stata

In this article, we describe qregsel, a community-contributed command that implements a copula-based sample-selection correction for quantile regression recently proposed by Arellano and Bonhomme (2017, Econometrica 85: 1–28). The command allows the user to model selection in quantile regressions by using either a Gaussian or a one-dimensional Frank copula. We illustrate the use of qregsel with two examples. First, we apply the method to the fictional dataset used in the Stata Base Reference Manual for the heckman command. Second, we replicate part of the empirical application of the original article using data for the United Kingdom that cover the period 1978–2000 to compare wages of males and females at different quantiles.

Food Security and Sustainability: Discussing the Four Pillars to Encompass Other Dimensions

The unadjusted intake of food constitutes a real challenge for the several sustainability dimensions. In this perspective, the main objectives of this research are to characterise the current contexts of food security, its relationship with sustainability, and identify proposals and actions that may support the design of more adjusted policies in the future. In addition, it is intended to assess if the food security pillars properly address the sustainability goals and if the evolution of undernutrition is accompanied by sustainable frameworks. In this way, statistical information from the FAOSTAT database was considered for the several dimensions of food security over the period 2000–2020. These data were analysed through factor-cluster approaches and panel data methodologies, namely those related to quantile regressions. As main insights, we may refer that undernutrition is more impacted by the availability of food and nutrients and political stability than by the level of GDP—Gross Domestic Product (except for the extreme cases). This means that the level of development is not the primary explanation for the problems of nutrition. The main focus of the national and international policies must be to improve the agrifood supply chains and to support political stability, in order to mitigate undernutrition worldwide and ensure a global access to sustainable and healthy diets. In addition, it is suggested to rethink the four pillars of food security (availability, access, utilisation and stability), in order to encompass other dimensions, such as climate change.

Nexus of Bank Income Structure and Risk: Evidence from Balkans

In this study, we analysed the income structure of the 30 largest banks in seven Balkan countries in the period before, during and after the global economic crisis. Considering that the structure of income primarily consists of interest-bearing and non-interest-bearing income, we analysed whether the crisis has affected the change in the structure of banks’ income in the Balkans. To analyse this, we used panel and quantile regressions models. The study additionally implemented quantile regression for checking the robustness. The results show that there is a more significant correlation between non-interest-bearing and interest-bearing income, while the correlation with net profit is more moderate. According to our results, the interest income grew in the period when reference interest rates fell and when the negative effects of the economic crisis were most pronounced. The banks in the region of the Balkans built their profits more on interest-incomes in the period before and after the economic crisis.

BEHAVIOR AND INFLUENCE MECHANISMS OF ENTERPRISES USING GOVERNMENT SUBSIDIES: EVIDENCE FROM CHINA

This study investigates the effects of different subsidy use patterns on economic performance, the effect mechanisms, and differences among enterprises with heterogeneous economic performance. A theoretical model is built to analyze the factors influencing subsidy use. Applying ordinary least squares and panel quantile regressions on panel data of China’s 3,565 A-share listed companies from 2007 to 2017, we find that subsidies can significantly improve economic performance. Specifically, enterprises usually use subsidies in three different ways (i.e. R&D input, expansion of production capacity for existing products, and human resource training), and the positive impact of these three use patterns on economic performance is moderated by two factors (i.e. the proportions of both R&D operating expenses and human resource training cost) in different degrees. Moreover, the effects are more significant in the lower quantile of economic performance; hence, heterogeneity of economic performance must be considered when formulating relevant policies.

COMPLETE SUBSET AVERAGING FOR QUANTILE REGRESSIONS

We propose a novel conditional quantile prediction method based on complete subset averaging (CSA) for quantile regressions. All models under consideration are potentially misspecified, and the dimension of regressors goes to infinity as the sample size increases. Since we average over the complete subsets, the number of models is much larger than the usual model averaging method which adopts sophisticated weighting schemes. We propose to use an equal weight but select the proper size of the complete subset based on the leave-one-out cross-validation method. Building upon the theory of Lu and Su (2015, Journal of Econometrics 188, 40–58), we investigate the large sample properties of CSA and show the asymptotic optimality in the sense of Li (1987, Annals of Statistics 15, 958–975) We check the finite sample performance via Monte Carlo simulations and empirical applications.

Growth at Risk From Climate Change

How will climate change affect risks to economic activity? Research on climate impacts has tended to focus on effects on the average level of economic growth. I examine whether climate change may make severe contractions in economic activity more likely using quantile regressions linking growth to temperature. The effects of temperature on downside risks to economic growth are large and robust across specifications. These results suggest the growth at risk from climate change is large—climate change may make economic contractions more likely and severe and thereby significantly impact economic and financial stability and welfare.