Reverse mortgages through artificial intelligence: new opportunities for the actuaries

Decisions in Economics and Finance - In its basic structure, the reverse mortgage (RM) is a contract where a home owner borrows a part or the totality of the future liquidation value of his home at...     

Tax Reform,Sector‐specific Labor Supply and Welfare Effects*

This paper focuses in particular on the 1992 tax reform in Norway. In this reform the top marginal tax rates were cut considerably. We find that the impact on overall labor supply is rather modest, but these modest changes shadow for stronger sectoral changes. The tax reform stimulated the women to shift their labor from the public to the private sector and to work longer hours. A calculation of mean compensated variation, calculated within the framework of a random utility model, shows that the richest households benefited far more from the 1992 tax reform than did the poorest households.     

Quantile regression estimates and the analysis of structural breaks

The paper considers a test for structural breaks based on quantile regressions instead of OLS estimates. Besides granting robustness, this allows us to verify the impact of a break in more than one point of the conditional distribution. The quantile regression test is then repeatedly implemented as a diagnostic tool to uncover partial or spurious breaks. The test is also implemented to measure the contribution of each explanatory variable to the instability of the regression coefficients, thus finding which one of the different possible sources of breaks linked to the nature of the explanatory variables is the most effective. A real data example of exchange rates shows the presence of a time-driven break, but only at the lower quartile, while the analysis of the explanatory variable excludes its involvement in the break. Since the asymptotic distribution of the OLS test for structural change depends on i.i.d. normal errors and on the exogeneity of the explanatory variables, a Monte Carlo study analyses the behavior of OLS and quantile regression tests for structural changes with lagged endogenous variables, non-normal errors, spurious or partial breaks, and misspecification.     

Correction to: Foreword special issue Deaf 2019–Maf 2018

Decisions in Economics and Finance -     

Temporary Migration and Foreign Direct Investment

The question of complementarity or substitutability of FDI and international labour mobility has not yet been answered. The substitutability assumption does not take into consideration the technological spillover of FDI in the host countries. Moreover, migration flows reveal cultural characteristics and labour force properties of their native country which may stimulate bilateral business networks, strengthening the complementarity assumption between capital and labour flows. In this paper we build a continuous time dynamic model where these offsetting forces are at work. We analyze whether, and to what extent, the increase in labour mobility might affect FDI outflows. A numerical simulation is performed showing that a higher income growth rate corresponds to a higher labour mobility. Some policy implications and further research direction are suggested.     

Decomposition and wage inequality

Earning differentials are investigated by a quantile regressions based decomposition, which disentangles the inequalities linked to the covariates and coefficients at various quantiles. Gender and region are considered the main sources of inequality. The unexplained gender and regional differences decrease at the highest wages. Their combination at the lower wages’ level affects women more, causing a so-called sticky floor. Gender and regional covariate effects show a prevalence of women covariates compared with the men’s group, and a prevalence of southern women covariates within the women’s group, particularly at the higher quantiles. This can be interpreted as a glass ceiling hindering southern women at higher wages.     

The synthetic control approach: Multivalued treatments at the quantiles

The synthetic control approach to analyze policy impact is here complemented to compute i) multivalued treatment effects and ii) treatment effect evaluated at different levels of the distribution of the treated, at the various quantiles. Confining the analysis to binary treatment and/or to average values alone can be very misleading since treatments can be multivalued and they can have different impact away from the mean, in the tails. Two case studies and a set of simulations allow to investigate the behavior of the proposed approach.