Upskilling and distributional changes in the electronics global value chain

The electronics industry has one of the most complex global production chains in the international economy. Using data from the World Input–Output Database for the period 2000–14, this article traces individual contributions to the value chain in order to observe how financial turmoil has affected its evolution over time and to map international interactions. The authors point to a rise in offshoring until the outbreak of the global financial crisis of 2007–08, as China and other Eastern Asian economies became an essential node of value creation. They also detect a deep transformation of production technologies, accompanied by a process of upskilling.     

Reliable error estimation for Sobol’ indices

In the field of sensitivity analysis, Sobol’ indices are sensitivity measures widely used to assess the importance of inputs of a model to its output. The estimation of these indices is often performed through Monte Carlo or quasi-Monte Carlo methods. A notable method is the replication procedure that estimates first-order indices at a reduced cost in terms of number of model evaluations. An inherent practical problem of this estimation is how to quantify the number of model evaluations needed to ensure that estimates satisfy a desired error tolerance. This article addresses this challenge by proposing a reliable error bound for first-order and total effect Sobol’ indices. Starting from the integral formula of the indices, the error bound is defined in terms of the discrete Walsh coefficients of the different integrands. We propose a sequential estimation procedure of Sobol’ indices using the error bound as a stopping criterion. The sequential procedure combines Sobol’ sequences with either Saltelli’s strategy to estimate both first-order and total effect indices, or the replication procedure to estimate only first-order indices.     

Regulation of migrant entrepreneurship: The strained conjunction of laws,policies and practices

We are struck by a curious paradox: the flourishing discourse on migrant entrepreneurship is replete with references to the regulatory environment; yet the precise ways in which regulations exert influence is rarely spelt out. This task is all the more urgent because policymakers are alighting on the fact that migrants often turn to self-employment to make their way in destination societies. Yet, the extent to which regulations – comprising laws and governmental and non-governmental policy measures and practices – is poorly understood. This special section aims at filling this gap by adopting a theoretically informed analytical perspective to understand the role of regulation in migrant entrepreneurship. Articles in this special section analyse the nature of laws, policies and practices, the factors of success/failure of these, the role of governmental and non-governmental actors, and the effect of different welfare regimes and governance conditions.     

The Integration of Interstate Migrants in India: A 7 State Policy Evaluation

Interstate migration in developing countries is a key income generating strategy for low-income households. In India, despite the importance of migration between states, interstate migrants continue to face significant integration barriers in their destination states. The impact of state borders on migration within India is significant and large. This study presents one of the first attempts at creating a set of indicators to understand the role of state-level policies for the integration of interstate migrants in a developing country. After illustrating the process behind the creation of this tool and the tool in itself, we compare seven of the major migrant destination states of India, based on their policy frameworks relevant to the integration of interstate migrants. Out of these states, we found that Kerala state is the most inclusive of interstate migrants but that overall, policymakers in the considered Indian states have a long way to go to improve the integration of interstate migrants.     

Home care for the elderly: the role of relatives,friends and neighbors

We use data from the Survey of Health, Ageing and Retirement in Europe to examine the hours of home care received by the elderly. The existing empirical literature has mostly examined informal home care from children and formal home care. We identify two additional informal home care providers, namely, relatives (other than children) and friends (including neighbors) who provide about 30 % of the hours of informal home care. Our main new empirical finding is that single elderly persons who can rely less on children—and in particular daughters—for their home care receive not only more formal care but also more care from friends and neighbors. These findings suggest that policymakers need to take into account not only home care provision from children but also home care provision from friends and neighbors to obtain accurate projections concerning the increasing costs of formal care programs due to an aging population.     

Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration

A novel probabilistic numerical method for quantifying the uncertainty induced by the time integration of ordinary differential equations (ODEs) is introduced. Departing from the classical strategy to randomise ODE solvers by adding a random forcing term, we show that a probability measure over the numerical solution of ODEs can be obtained by introducing suitable random time steps in a classical time integrator. This intrinsic randomisation allows for the conservation of geometric properties of the underlying deterministic integrator such as mass conservation, symplecticity or conservation of first integrals. Weak and mean square convergence analysis is derived. We also analyse the convergence of the Monte Carlo estimator for the proposed random time step method and show that the measure obtained with repeated sampling converges in the mean square sense independently of the number of samples. Numerical examples including chaotic Hamiltonian systems, chemical reactions and Bayesian inferential problems illustrate the accuracy, robustness and versatility of our probabilistic numerical method.     

Delinquent Networks

Delinquents are embedded in a network of relationships. Each delinquent decides in a non‐cooperative way how much delinquency effort he will exert. We characterize the Nash equilibrium and derive an optimal enforcement policy, called the key‐player policy. We then extend our characterization of optimal single player network removal to optimal group removal, the key group. We also characterize and derive a policy that targets links rather than players. Finally, we endogenize the network connecting delinquents by allowing players to join the labor market instead of committing delinquent offenses. The key‐player policy turns out to be much more complex because it depends on wages and on the structure of the network. (JEL: A14, C72, K42, L14)     

A Stochastic Volatility Model With Realized Measures for Option Pricing

Abstract

Based on the fact that realized measures of volatility are affected by measurement errors, we introduce a new family of discrete-time stochastic volatility models having two measurement equations relating both observed returns and realized measures to the latent conditional variance. A semi-analytical option pricing framework is developed for this class of models. In addition, we provide analytical filtering and smoothing recursions for the basic specification of the model, and an effective MCMC algorithm for its richer variants. The empirical analysis shows the effectiveness of filtering and smoothing realized measures in inflating the latent volatility persistence—the crucial parameter in pricing Standard and Poor’s 500 Index options.     

Temporal aggregation of cyclical models with business cycle applications

This paper focuses on temporal aggregation of the cyclical component model as introduced by Harvey (1989). More specifically, it provides the properties of the aggregate process for any generic period of aggregation. As a consequence, the exact link between aggregate and disaggregate parameters can be easily derived. The cyclical model is important due to its relevance in the analysis of business cycle. Given this, two empirical applications are presented in order to compare the estimated parameters of the quarterly models for German and US gross domestic products with those of the corresponding models aggregated to annual frequency.