Mixed Signals: to what extent does male wage scarring vary with the characteristics of the local labour market in which unemployment was experienced?

I test the hypothesis that unemployment experienced in high unemployment regions is less likely to be viewed by employers as a negative productivity signal, and more as a characteristic of the region. This predicts that unemployment's short-run negative wage effects will be mitigated if experienced in high unemployment regions. If so, then what long-term implications does this have for future wage growth (Wage Scarring)? How important is regional heterogeneity in driving wage outcomes? Continuous work-life histories are matched to the regional context in which individuals reside. This novel data set permits control for the timing of career disruptions, as well as regional location at the time of displacement, whilst searching and at re-employment. Persistent wage penalties are found, conditional on previous labour market status. Seminal UK research concludes that the first spell of non-employment carries the highest penalty. Considering unemployment and inactivity, no reduction in the penalty associated with incidence of inactivity is found. Strong regional differences are found in the impact of redundancy on wage growth. This is contingent on labour market tight-ness and urbanity of the region in which unemployment was experienced. Redundancy followed by unemployment in areas of high economic activity is equally damaging for future earnings potential, independent of age. Moreover, robust evidence is found supporting the main hypothesis in the UK, on average and for over 45s made redundant in their previous jobs.job displacement, wage scarring, regional heterogeneity, work-life histories

Change, rigidity & delay in the UK system of land-use development control

The British system of development control is time-consuming and uncertain in outcome. Moreover, it is becoming increasingly overloaded as it has gradually switched away from being centred on a traditional ‘is it an appropriate land-use?’ type approach to one based on multi-faceted inspections of projects and negotiations over the distribution of the potential financial gains arising from them. Recent policy developments have centred on improving the operation of development control. This paper argues that more fundamental issues may be a stake as well. Important market changes have increased workloads. Furthermore, the UK planning system's institutional framework encourages change to move in specific directions, which is not always helpful. If expectations of increased long-term housing supply are to be met more substantial changes to development control may be essential but hard to achieve

Job seeker's allowance in Great Britain: How does the regional labour market affect the duration until job finding?

Employing a large individual-level administrative dataset from Great Britain, covering the period 1999-2007, we analyse the factors influencing the length of unemployment benefits claimant periods with subsequent transition to re-employment. To this end, this individual-level data is merged with a group of regional indicators to control for relevant regional labour market characteristics. From a methodological point of view, we adopt a flexible censored quantile regression approach to estimating conditional re-employment hazards. Our results indicate that the individual characteristics of an unemployed person are generally more im- portant than the regional labour market conditions. However, regional labour supply and demand conditions are important determinants for the length of unemployment compensation claim periods. Our analysis provides evidence that large cities such as London and Birmingham provide the worse local labour market conditions for job seekers allowance recipients, while remote regions like the Shetland islands perform among the best.benefit duration, quantile regression, hazard rate.

Housing supply and planning delay in the South of England

There is growing international interest in the impact of regulatory controls on the supply of housing The UK has a particularly restrictive planning regime and a detailed and uncertain process of development control linked to it. This paper presents the findings of empirical research on the time taken to gain planning permission for selected recent major housing projects from a sample of local authorities in southern England. The scale of delay found was far greater than is indicated by average official data measuring the extent to which local authorities meet planning delay targets. If these results are representative of the country as a whole, they indicate that planning delay could be a major cause of the slow responsiveness of British housing supply

Effective offline training and efficient online adaptation

Developing agents that behave intelligently in the world is an open challenge in machine learning. Desiderata for such agents are efficient exploration, maximizing long term utility, and the ability to effectively leverage prior data to solve new tasks. Reinforcement learning (RL) is an approach that is predicated on learning by directly interacting with an environment through trial-and-error, and presents a way for us to train and deploy such agents. Moreover, combining RL with powerful neural network function approximators – a sub-field known as “deep RL” – has shown evidence towards achieving this goal. For instance, deep RL has yielded agents that can play Go at superhuman levels, improve the efficiency of microchip designs, and learn complex novel strategies for controlling nuclear fusion reactions. A key issue that stands in the way of deploying deep RL is poor sample efficiency. Concretely, while it is possible to train effective agents using deep RL, the key successes have largely been in environments where we have access to large amounts of online interaction, often through the use of simulators. However, in many real-world problems, we are confronted with scenarios where samples are expensive to obtain. As has been alluded to, one way to alleviate this issue is through accessing some prior data, often termed “offline data”, which can accelerate how quickly we learn such agents, such as leveraging exploratory data to prevent redundant deployments, or using human-expert data to quickly guide agents towards promising behaviors and beyond. However, the best way to incorporate this data into existing deep RL algorithms is not straightforward; naïvely pre-training using RL algorithms on this offline data, a paradigm called “offline RL” as a starting point for subsequent learning is often detrimental. Moreover, it is unclear how to explicitly derive useful behaviors online that are positively influenced by this offline pre-training. With these factors in mind, this thesis follows a 3-pronged strategy towards improving sample-efficiency in deep RL. First, we investigate effective pre-training on offline data. Then, we tackle the online problem, looking at efficient adaptation to environments when operating purely online. Finally, we conclude with hybrid strategies that use offline data to explicitly augment policies when acting online

Einstein and nazi physics : When science meets ideology and prejudice

In the 1920s and 30s, in a Germany with widespread and growing anti-Semitism, and later with the rise of Nazism, Albert Einstein?s physics faced hostility and was attacked on racial grounds. That assault was orchestrated by two Nobel laureates in physics, who asserted that stereotypical racial features are exhibited in scientific thinking. Their actions show how ideology can infect and inflect science. Reviewing this episode in the current context remains an instructive and cautionary tale

Science and ideology : the case of physics in nazi Germany

Science is not «above» politics and ethics: it is intrinsically political, and constantly raises ethical dilemmas. The consequences of evading such issues were made particularly clear in the actions of scientists working in Nazi Germany in the 1930s and 40s. The accusation in 2006 that Dutch physicist Peter Debye was an opportunist who colluded with the Nazis reopened the debate about the conduct of physicists at that time. Here I consider what those events can tell us about the relationship of science and politics today. I argue that an insistence that science is an abstract, apolitical inquiry into nature is a myth that can leave it morally compromised and vulnerable to political manipulation

Construction of a linked postcode district to regional-level dataset for Great Britain.

A one-to-one link is developed between overlapping sub-regional entities using geographical tools newly available to the Economic Research Community. The aim of this project is to create a database exploiting the geographical variation in publicly available data, in order to better control for regional heterogeneity. The database covers the period 1995 to 2007, and includes regional identiers at the postcode district, Local Authority, NUTS3 and Travel-To-Work Area levels of aggregation. Roughly 160 controls are available to the researcher. This data could be used to provide new insights for Regional Policy Analysis. An example of an application of this resource in the context of unemployment duration can be found in (Ball and Wilke, 2009) for the UK.Regional data, Great Britain, Overlapping regional entities, Regional heterogeneity.