A Survey of Differentially Private Regression for Clinical and Epidemiological Research

Differential privacy is a framework for data analysis that provides rigorous privacy protections for database participants. It has increasingly been accepted as the gold standard for privacy in the analytics industry, yet there are few techniques suitable for statistical inference in the health sciences. This is notably the case for regression, one of the most widely used modelling tools in clinical and epidemiological studies. This paper provides an overview of differential privacy and surveys the literature on differentially private regression, highlighting the techniques that hold the most relevance for statistical inference as practiced in clinical and epidemiological research. Research gaps and opportunities for further inquiry are identified.     

IDIOSYNCRATIC AND AGGREGATE RISKS,INEQUALITY AND GROWTH

The paper disaggregates productivity shocks at a firm level into idiosyncratic and aggregate risks, and studies their impacts on inequality, growth and welfare. It develops a growth model with human capital and incomplete insurance and credit markets that provides a closed‐form solution for income inequality dynamics. We find that uninsured idiosyncratic risks are the most important determinants of inequality, growth and welfare. They are the source of nondegenerate wealth distribution. A lower weight of these shocks leads to lower steady‐state inequality, higher growth and welfare. A redistribution of income that serves as social insurance against such risks increases welfare and decreases inequality. But, it also decreases growth by distorting individual consumption and saving decisions.     

Specification of Distance Functions Using Semi- and Nonparametric Methods with an Application to the Dynamic Performance of Eastern and Western European Air Carriers

In this paper we examine the productive performance of a group of three East European carriers and compare it to thirteen of their West European competitors during the period 1977–1990. We first model the multiple output/multiple input technology with a stochastic distance frontier using recently developed semiparametric efficient methods. The endogeneity of multiple outputs is addressed in part by introducing multivariate kernel estimators for the joint distribution of the multiple outputs and potentially correlated firm random effects. We augment estimates from our semiparametric stochastic distance function with nonparametric distance function methods, using linear programming techniques, as well as with extended decomposition methods, based on the Malmquist index number. Both semi- and nonparametric methods indicate significant slack in resource utilization in the East European carriers relative to their Western counterparts, and limited convergence in efficiency or technical change between them. The implications are rather stark for the long run viability of the East European carriers in our sample.     

Waste disclosure and corporate cash holdings

ABSTRACT

In this paper, we address an important and emerging question: Can firms’ voluntary waste disclosure affect corporate cash holdings? Using a sample of S&P 500 firms, we find strong evidence for a positive relationship between waste disclosure and the cash holding policy of firms. Furthermore, we find that waste disclosure significantly increases cash holdings only for firms with strong corporate governance quality. We also find that the significant relationship between waste disclosure and cash holdings remains unchanged only for firms that operate in environmentally sensitive industries. Our paper provides novel evidence on the role of voluntary waste disclosure as an environmental dimension that influences the cash policy of firms and highlights the little-known issue of waste disclosure as a significant research topic.