Social Interaction and Intergenerational Skill Transfer

We explore the relationship between educational attainment and social interaction using individual level data from the British National Child Development Study. To be specific, we analyze whether an intergenerational aspect to this relationship exists by examining the relationship between the educational attainment of children and the degree of formal social activity undertaken by their parents. In accordance with the existing literature, our results support a positive association between education and social interaction. Furthermore, our results suggest that children´s scores in reading, mathematics and vocabulary tests are positively associated with the extent of their parents´ formal social interaction. This relationship is robust to controlling for the degree of intra-family based social interaction and the social activities of the child

Patient Mobility, Health Care Quality and Welfare.

Patient mobility is a key issue in the EU who recently passed a new law on patients’right to EU-wide provider choice. In this paper we use a Hotelling model with two regions that differ in technology to study the impact of patient mobility on health care quality, health care financing and welfare. A decentralised solution without patient mobility leads to too low (high) quality and too few (many) patients being treated in the high-skill (low-skill) region. A centralised solution with patient mobility implements the first best, but the low-skill region would not be willing to transfer authority as its welfare is lower than without mobility. In a decentralised solution, the effects of patient mobility depend on the transfer payment. If the payment is below marginal cost, mobility leads to a ‘race-to-the-bottom’in quality and lower welfare in both regions. If the payment is equal to marginal cost, quality and welfare remain unchanged in the high-skill region, but the low-skill region bene…ts. For a socially optimal payment, which is higher than marginal cost, quality levels in the two regions are closer to (but not at) the …rst best, but welfare is lower in the low-skill region. Thus, patient mobility can have adverse effects on quality provision and welfare unless an appropriate transfer payment scheme is implemented.Patient mobility; Health care quality; Regional and global welfare.

Analyzing the Effectiveness of University Technology Transfer: Implications for Entrepreneurship Education

We review and synthesize the burgeoning literature on institutions and agents engaged in the commercialization of university-based intellectual property. These studies indicate that institutional incentives and organizational practices both play an important role in enhancing the effectiveness of technology transfer. We conclude that university technology transfer should be considered from a strategic perspective. Institutions that choose to stress the entrepreneurial dimension of technology transfer need to address skill deficiencies in technology transfer offices (TTOs), reward systems that are inconsistent with enhanced entrepreneurial activity, and education/training for faculty members, post-docs, and graduate students relating to interactions with entrepreneurs. Business schools at these universities can play a major role in addressing these skill and educational deficiencies, through the delivery of targeted programs to technology licensing officers and members of the campus community wishing to launch startup firms.

Neural Skill Transfer from Supervised Language Tasks to Reading Comprehension

Reading comprehension is a challenging task in natural language processing and requires a set of skills to be solved. While current approaches focus on solving the task as a whole, in this paper, we propose to use a neural network `skill' transfer approach. We transfer knowledge from several lower-level language tasks (skills) including textual entailment, named entity recognition, paraphrase detection and question type classification into the reading comprehension model. We conduct an empirical evaluation and show that transferring language skill knowledge leads to significant improvements for the task with much fewer steps compared to the baseline model. We also show that the skill transfer approach is effective even with small amounts of training data. Another finding of this work is that using token-wise deep label supervision for text classification improves the performance of transfer learning

The Unintended Consequences of Encouraging Work: Tax Incidence and the EITC

The EITC is designed to encourage work. But EITC-induced increases in labor supply may drive wages down, shifting the intended transfer toward employers and hurting non- EITC low-skill workers. I exploit variation across family types and skill levels to identify the eect of a large EITC expansion in the mid 1990s. Ceteris paribus, low-skill single mothers keep only $0.70 of every dollar they receive. Employers of low-skill labor capture$0.72, $0.30 from single mothers plus$0.43 from ineligible workers whose after-tax incomes fall when the EITC is expanded. The net transfer to low-skill workers is less than $0.28 per dollar spent.

A Deep Hierarchical Approach to Lifelong Learning in Minecraft

We propose a lifelong learning system that has the ability to reuse and transfer knowledge from one task to another while efficiently retaining the previously learned knowledge-base. Knowledge is transferred by learning reusable skills to solve tasks in Minecraft, a popular video game which is an unsolved and high-dimensional lifelong learning problem. These reusable skills, which we refer to as Deep Skill Networks, are then incorporated into our novel Hierarchical Deep Reinforcement Learning Network (H-DRLN) architecture using two techniques: (1) a deep skill array and (2) skill distillation, our novel variation of policy distillation (Rusu et. al. 2015) for learning skills. Skill distillation enables the HDRLN to efficiently retain knowledge and therefore scale in lifelong learning, by accumulating knowledge and encapsulating multiple reusable skills into a single distilled network. The H-DRLN exhibits superior performance and lower learning sample complexity compared to the regular Deep Q Network (Mnih et. al. 2015) in sub-domains of Minecraft

Is there a Case for Public Provision of Private Goods if Preferences are Heterogeneous? An Example with Day Care

A strong case for public provision of certain private goods has been established for an economy in which individuals have homogeneous preferences but differ in skill levels. There has been a critique of this model/mechanism arguing that heterogeneous preferences at a given skill level would invalidate the mechanism, implying that public provision of private goods is merely of theoretical, not of practical interest. The argument is that if the public provision level is set so as to fit the low skill person with a high preference for the publicly provided good, the low skill person with a low preference for the good comes out worse than in a system without public provision. In this paper we take this critique seriously and investigate if a public provision scheme can be constructed so that we obtain a strict Pareto improvement when going from a pure tax/transfer system to the public provision scheme even if preferences are heterogeneous. We find that heterogeneous preferences do not invalidate the benefits of publicly provided private goods. We also characterise the optimum tax and public provision policy.public provision, private goods, in-kind transfer, heterogeneous preferences, day care

Automating human skills : preliminary development of a human factors methodology to capture tacit cognitive skills

Despite technological advances in intelligent automation, it remains difficult for engineers to discern which manual tasks, or task components, would be most suitable for transfer to automated alternatives. This research aimed to develop an accurate methodology for the measurement of both observable and unobservable physical and cognitive activities used in manual tasks for the capture of tacit skill. Experienced operators were observed and interviewed in detail, following which, hierarchical task analysis and task decomposition methods were used to systematically explore and classify the qualitative data. Results showed that a task analysis / decomposition methodology identified different types of skill (e.g. procedural or declarative) and knowledge (explicit or tacit) indicating this methodology could be used for further human skill capture studies. The benefit of this research will be to provide a methodology to capture human skill so that complex manual tasks can be more efficiently transferred into automated processes