Caught in the Bulimic Trap? Persistence and State Dependence of Bulimia Among Young Women

Eating disorders are an important and growing health concern, and bulimia nervosa (BN) accounts for the largest fraction of eating disorders. Health consequences of BN are substantial and especially serious given the increasingly compulsive nature of the disorder. However, remarkably little is known about the mechanisms underlying the persistent nature of BN. Using a unique panel data set on young women and instrumental variable techniques, we document that unobserved heterogeneity plays a role in the persistence of BN, but strikingly up to two thirds is due to true state dependence. Our results, together with support from the medical literature, provide evidence that bulimia should be considered an addiction. Our findings have important implications for public policy since they suggest that the timing of the policy is crucial: preventive educational programs should be coupled with more intense (rehabilitation) treatment at the early stages of bingeing and purging behaviors. Our results are robust to different model specifications and identifying assumptions.bulimia nervosa, demographics, state dependence, instrumental variables, dynamic panel data estimation, addiction

Caught in the Bulimic Trap? Persistence and State Dependence of Bulimia Among Young Women

Eating disorders are an important and growing health concern, and bulimia nervosa (BN) accounts for the largest fraction of eating disorders. Health consequences of BN are substantial and especially serious given the increasingly compulsive nature of the disorder. However, remarkably little is known about the mechanisms underlying the persistent nature of BN. Using a unique panel data set on young women and instrumental variable techniques, we document that unobserved heterogeneity plays a role in the persistence of BN, but strikingly up to two thirds is due to true state dependence. Our findings have important implications for public policy since they suggest that the timing of the policy is crucial: preventive educational programs should be coupled with more intense (rehabilitation) treatment at the early stages of bingeing and purging behaviors. Our results are robust to different model specifications and identifying assumptions.Bulimia Nervosa, Demographics, State Dependence, Instrumental Variables, Dynamic Panel Data Estimation, and Addiction

The liberalisation of the European gas market and its consequences for Russia

Russia is the world's biggest natural gas producer, with output of 581 bn m3 in 2001, and is also a key supplier of the European gas market (around 30% of current EU gas imports). Therefore gas exports rank with oil exports as an essential variable of Russian economic policy, and anyinstitutional evolution of its gas export markets is crucial for Russia's economy as well as its gas industry. Liberalisation of the European gas market will have major consequences for main suppliers, and therefore for Russia.LIBERALISATION ; MARCHE ; GAZ NATUREL ; RUSSIE ; EUROPE

Long-run Effects of Public Sector Sponsored Training in West Germany

Between 1991 and 1997 West Germany spent on average about 3.6 bn Euro per year on public sector sponsored training programmes for the unemployed. We base our empirical analysis on a new administrative data base that plausibly allows for selectivity correction by microeconometric matching methods. We identify the effects of different types of training programmes over a horizon of more than seven years. Using bias corrected weighted multiple neighbours matching we find that all programmes have negative effects in the short run and positive effects over a horizon of about four years. However, for substantive training programmes with duration of about two years gains in employment probabilities of more than 10% points appear to be sustainable, but come at the price of large negative lock-in effects.Active labour market policy, matching estimation, programme evaluation, panel data.

Energy-Efficient Transmission Scheduling with Strict Underflow Constraints

We consider a single source transmitting data to one or more receivers/users over a shared wireless channel. Due to random fading, the wireless channel conditions vary with time and from user to user. Each user has a buffer to store received packets before they are drained. At each time step, the source determines how much power to use for transmission to each user. The source's objective is to allocate power in a manner that minimizes an expected cost measure, while satisfying strict buffer underflow constraints and a total power constraint in each slot. The expected cost measure is composed of costs associated with power consumption from transmission and packet holding costs. The primary application motivating this problem is wireless media streaming. For this application, the buffer underflow constraints prevent the user buffers from emptying, so as to maintain playout quality. In the case of a single user with linear power-rate curves, we show that a modified base-stock policy is optimal under the finite horizon, infinite horizon discounted, and infinite horizon average expected cost criteria. For a single user with piecewise-linear convex power-rate curves, we show that a finite generalized base-stock policy is optimal under all three expected cost criteria. We also present the sequences of critical numbers that complete the characterization of the optimal control laws in each of these cases when some additional technical conditions are satisfied. We then analyze the structure of the optimal policy for the case of two users. We conclude with a discussion of methods to identify implementable near-optimal policies for the most general case of M users.Comment: 109 pages, 11 pdf figures, template.tex is main file. We have significantly revised the paper from version 1. Additions include the case of a single receiver with piecewise-linear convex power-rate curves, the case of two receivers, and the infinite horizon average expected cost proble

Flexible Queueing Architectures

We study a multi-server model with $n$ flexible servers and $n$ queues, connected through a bipartite graph, where the level of flexibility is captured by the graph's average degree, $d_n$. Applications in content replication in data centers, skill-based routing in call centers, and flexible supply chains are among our main motivations. We focus on the scaling regime where the system size $n$ tends to infinity, while the overall traffic intensity stays fixed. We show that a large capacity region and an asymptotically vanishing queueing delay are simultaneously achievable even under limited flexibility ($d_n \ll n$). Our main results demonstrate that, when $d_n\gg \ln n$, a family of expander-graph-based flexibility architectures has a capacity region that is within a constant factor of the maximum possible, while simultaneously ensuring a diminishing queueing delay for all arrival rate vectors in the capacity region. Our analysis is centered around a new class of virtual-queue-based scheduling policies that rely on dynamically constructed job-to-server assignments on the connectivity graph. For comparison, we also analyze a natural family of modular architectures, which is simpler but has provably weaker performance.Comment: Revised October 2016. A preliminary version of this paper appeared at the 2013 ACM Sigmetrics conference; the performance of the architectures proposed in the current paper is significantly better than the one in the conference versio

Finite Horizon Online Lazy Scheduling with Energy Harvesting Transmitters over Fading Channels

Lazy scheduling, i.e. setting transmit power and rate in response to data traffic as low as possible so as to satisfy delay constraints, is a known method for energy efficient transmission.This paper addresses an online lazy scheduling problem over finite time-slotted transmission window and introduces low-complexity heuristics which attain near-optimal performance.Particularly, this paper generalizes lazy scheduling problem for energy harvesting systems to deal with packet arrival, energy harvesting and time-varying channel processes simultaneously. The time-slotted formulation of the problem and depiction of its offline optimal solution provide explicit expressions allowing to derive good online policies and algorithms