How Changes in Benefits Entitlement Affect the Duration of Unemployment

This paper investigates the disincentive effects of the potential duration of unemployment insurance (UI) benefits.The disincentive effects are identified by exploiting changes in the UI system in Slovenia, which involved substantial reductions in the potential benefit duration and had characteristics of a "natural experiment".We find that the change had a positive effect on the exit rate out of unemployment - both to employment and to other destinations - at various durations of unemployment spells and for many categories of unemployed workers.Unemployment Insurance;potential benefit duration;job finding rates

Incentive Effects of Unemployment Insurance Savings Accounts: Evidence from Chile

This study examines the determinants of job-finding rates of unemployment benefit recipients under the Chilean program. This is a unique, innovative program that combines social insurance through a solidarity fund (SF) with self-insurance in the form of unemployment insurance savings accounts (UISAs) - so as to mitigate the moral hazard problem of traditional unemployment insurance programs. Our study is the first one to empirically investigate whether UISAs improve work incentives. We find that for beneficiaries using the SF, the pattern of job finding rates over the duration of unemployment is consistent with moral hazard effects, while for beneficiaries relying on UISAs, the pattern is free of such effects. We also find that for benefit recipient not entitled to use the SF, the amount of accumulation on the UISA does not affect the exit rate from unemployment, suggesting that such individuals internalize the costs of unemployment benefts. Our results provide strong support to the idea that UISAs can improve work incentives.Unemployment insurance;unemployment duration;savings accounts

Match memory recurrent networks

Imbuing neural networks with memory and attention mechanisms allows for better generalisation with fewer data samples. By focusing only on the relevant parts of data, which is encoded in an internal 'memory' format, the network is able to infer better and more reliable patterns. Most neuronal attention mechanisms are based on internal networks structures that impose a similarity metric (e.g., dot-product), followed by some (soft-)max operator. In this paper, we propose a novel attention method based on a function between neuron activities, which we term a 'match function', which is augmented by a recursive softmax function. We evaluate the algorithm on the bAbI question answering dataset and show that it has stronger performance when only one memory hop is used in both terms of average score and in terms the number of solved questions. Furthermore, with three memory hops, our algorithm can solve 12/20 benchmark questions using 1000 training samples per task. This is an improvement on the previous state of the art of 9/20 solved questions, which was held by end-to-end memory networks

Convolutional-Match Networks for Question Answering

In this paper, we present a simple, yet effective, attention and memory mechanism that is reminis- cent of Memory Networks and we demonstrate it in question-answering scenarios. Our mechanism is based on four simple premises: a) memories can be formed from word sequences by using convo- lutional networks; b) distance measurements can be taken at a neuronal level; c) a recursive soft- max function can be used for attention; d) extensive weight sharing can help profoundly. We achieve state-of-the-art results in the bAbI tasks, outper- forming Memory Networks and the Differentiable Neural Computer, both in terms of accuracy and stability (i.e. variance) of results

The EPICS Software Framework Moves from Controls to Physics

The Experimental Physics and Industrial Control System (EPICS), is an open-source software framework for high-performance distributed control, and is at the heart of many of the world’s large accelerators and telescopes. Recently, EPICS has undergone a major revision, with the aim of better computing supporting for the next generation of machines and analytical tools. Many new data types, such as matrices, tables, images, and statistical descriptions, plus users’ own data types, now supplement the simple scalar and waveform types of the former EPICS. New computational architectures for scientific computing have been added for high-performance data processing services and pipelining. Python and Java bindings have enabled powerful new user interfaces. The result has been that controls are now being integrated with modelling and simulation, machine learning, enterprise databases, and experiment DAQs. We introduce this new EPICS (version 7) from the perspective of accelerator physics and review early adoption cases in accelerators around the world

How Changes in Benefits Entitlement Affect the Duration of Unemployment

This paper investigates the disincentive effects of the potential duration of unemployment insurance (UI) benefits.The disincentive effects are identified by exploiting changes in the UI system in Slovenia, which involved substantial reductions in the potential benefit duration and had characteristics of a "natural experiment".We find that the change had a positive effect on the exit rate out of unemployment - both to employment and to other destinations - at various durations of unemployment spells and for many categories of unemployed workers.

Shortening the Potential Duration of Unemployment Benefits does not affect the Quality of Post-Unemployed Jobs:Evidence from a Natural Experiment

This paper investigates how the potential duration of unemployment benefits affects the quality of post-unemployment jobs.It takes advantage of a natural experiment introduced by a change in Slovenia's unemployment insurance law that substantially reduced the potential benefit duration.Although this reduction strongly increased job finding rates, the quality of the postunemployment jobs remained unaffected: the paper finds that the law change had no effect on either the type of the contract (temporary vs. permanent), the duration of the post-unemployment jobs, or the wage earned in this job.

Incentive Effects of Unemployment Insurance Savings Accounts:Evidence from Chile

This study examines the determinants of job-finding rates of unemployment benefit recipients under the Chilean program. This is a unique, innovative program that combines social insurance through a solidarity fund (SF) with self-insurance in the form of unemployment insurance savings accounts (UISAs) - so as to mitigate the moral hazard problem of traditional unemployment insurance programs. Our study is the first one to empirically investigate whether UISAs improve work incentives. We find that for beneficiaries using the SF, the pattern of job finding rates over the duration of unemployment is consistent with moral hazard effects, while for beneficiaries relying on UISAs, the pattern is free of such effects. We also find that for benefit recipient not entitled to use the SF, the amount of accumulation on the UISA does not affect the exit rate from unemployment, suggesting that such individuals internalize the costs of unemployment benefts. Our results provide strong support to the idea that UISAs can improve work incentives.