Outsourcing and Volatility

While outsourcing of production from the U.S. to Mexico has been hailed in Mexico as a valuable engine of growth, recently there have been misgivings regarding its fickleness and volatility. This paper is among the first in the trade literature to study the second moment properties of outsourcing. We begin by documenting a new stylized fact: the maquiladora outsourcing industries in Mexico experience fluctuations in value added that are roughly twice as volatile as the corresponding industries in the U.S. A difference-in-difference method is extended to second moments to verify the statistical significance of this finding. We then develop a stochastic model of outsourcing with heterogeneous firms that can explain this volatility. The model employs two novel mechanisms: an extensive margin in outsourcing which responds endogenously to transmit shocks internationally, and translog preferences which modulate firm entry.

Timing and spectral studies of the transient X-ray pulsar EXO 053109-6609.2 with ASCA and Beppo-SAX

We report timing and spectral properties of the transient Be X-ray pulsar EXO 053109--6609.2 studied using observations made with the ASCA and BeppoSAX observatories. Though there must have been at least one spin-down episode of the pulsar since its discovery, the new pulse period measurements show a monotonic spin-up trend since 1996. The pulse profile is found to have marginal energy dependence. There is also evidence for strong luminosity dependence of the pulse profile, a single peaked profile at low luminosity that changes to a double peaked profile at high luminosity. This suggests a change in the accretion pattern at certain luminosity level. The X-ray spectrum is found to consist of a simple power-law with photon index in the range of 0.4--0.8. At high intensity level the spectrum also shows presence of weak iron emission line.Comment: 12 pages, 8 figures, Accepted for publication in Ap

Ecosystem respiration: Drivers of daily variability and background respiration in lakes around the globe

We assembled data from a global network of automated lake observatories to test hypotheses regarding the drivers of ecosystem metabolism. We estimated daily rates of respiration and gross primary production (GPP) for up to a full year in each lake, via maximum likelihood fits of a free‐water metabolism model to continuous high‐frequency measurements of dissolved oxygen concentrations. Uncertainties were determined by a bootstrap analysis, allowing lake‐days with poorly constrained rate estimates to be down‐weighted in subsequent analyses. GPP and respiration varied considerably among lakes and at seasonal and daily timescales. Mean annual GPP and respiration ranged from 0.1 to 5.0 mg O2 L−1 d−1 and were positively related to total phosphorus but not dissolved organic carbon concentration. Within lakes, significant day‐to‐day differences in respiration were common despite large uncertainties in estimated rates on some lake‐days. Daily variation in GPP explained 5% to 85% of the daily variation in respiration after temperature correction. Respiration was tightly coupled to GPP at a daily scale in oligotrophic and dystrophic lakes, and more weakly coupled in mesotrophic and eutrophic lakes. Background respiration ranged from 0.017 to 2.1 mg O2 L−1 d−1 and was positively related to indicators of recalcitrant allochthonous and autochthonous organic matter loads, but was not clearly related to an indicator of the quality of allochthonous organic matter inputs

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures

A Global lake ecological observatory network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate processbased ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest

The Promise of Prediction Markets

Prediction markets are markets for contracts that yield payments based on the outcome of an uncertain future event, such as a presidential election. Using these markets as forecasting tools could substantially improve decision making in the private and public sectors. We argue that U.S. regulators should lower barriers to the creation and design of prediction markets by creating a safe harbor for certain types of small stakes markets. We believe our proposed change has the potential to stimulate innovation in the design and use of prediction markets throughout the economy, and in the process to provide information that will benefit the private sector and government alike.Technology and Industry

The Global Lake Ecological Observatory Network (GLEON): the evolution of grassroots network science

Nine years later, with over 380 members from 40 countries, and 50 publications to its credit, GLEON is growing at a rapid pace and pushing the boundaries of the practice of network science. GLEON is really three networks: a network of lakes, data, and peopl

Heavy Mesons in Two Dimensions

The large mass limit of QCD uncovers symmetries that are not present in the QCD lagrangian. These symmetries have been applied to physical (finite mass) systems, such as B and D mesons. We explore the validity of this approximation in the 't Hooft model (two-dimensional QCD in the large-N approximation). We find that the large mass approximation is good, even at the charm mass, for form factors, but it breaks down for the pseudoscalar decay constant.Comment: 4 pages, 3 figures inc