Prices versus Quantities versus Bankable Quantities

Quantity-based regulation with banking allows regulated firms to shift obligations across time in response to periods of unexpectedly high or low marginal costs. Despite its wide prevalence in existing and proposed emission trading programs, banking has received limited attention in past welfare analyses of policy choice under uncertainty. We address this gap with a model of banking behavior that captures two key constraints: uncertainty about the future from the firm’s perspective and a limit on negative bank values (e.g., borrowing). We show conditions where banking provisions reduce price volatility and lower expected costs compared to quantity policies without banking. For plausible parameter values related to U.S. climate change policy, we find that bankable quantities produce behavior quite similar to price policies for about two decades and, during this period, improve welfare by about a $1 billion per year over fixed quantities.

Tracking Error and Active Portfolio Management

Persistent bear market conditions have led to a shift of focus in the tracking error literature. Until recently the portfolio allocation literature focused on tracking error minimization as a consequence of passive benckmark management under portfolio weights, transaction costs and short selling constraints. Abysmal benchmark performance shifted the literature's focus towards active portfolio strategies that aim at beating the benchmark while keeping tracking error within acceptable bounds. We investigate an active (dynamic) portfolio allocation strategy that exploits the predictability in the conditional variance-covariance matrix of asset returns. To illustrate our procedure we use Jorion's (2002) tracking error frontier methodology. We apply our model to a representative portfolio of Australian stocks over the period January 1999 through November 2002.

On optimal designs for clinical trials: An updated review

Optimization of clinical trial designs can help investigators achieve higher qualityresults for the given resource constraints. The present paper gives an overviewof optimal designs for various important problems that arise in different stages ofclinical drug development, including phase I dose–toxicity studies; phase I/II studiesthat consider early efficacy and toxicity outcomes simultaneously; phase IIdose–response studies driven by multiple comparisons (MCP), modeling techniques(Mod), or their combination (MCP–Mod); phase III randomized controlled multiarmmulti-objective clinical trials to test difference among several treatment groups;and population pharmacokinetics–pharmacodynamics experiments. We find thatmodern literature is very rich with optimal design methodologies that can be utilizedby clinical researchers to improve efficiency of drug development

Information-Theoretic Analysis of an Energy Harvesting Communication System

In energy harvesting communication systems, an exogenous recharge process supplies energy for the data transmission and arriving energy can be buffered in a battery before consumption. Transmission is interrupted if there is not sufficient energy. We address communication with such random energy arrivals in an information-theoretic setting. Based on the classical additive white Gaussian noise (AWGN) channel model, we study the coding problem with random energy arrivals at the transmitter. We show that the capacity of the AWGN channel with stochastic energy arrivals is equal to the capacity with an average power constraint equal to the average recharge rate. We provide two different capacity achieving schemes: {\it save-and-transmit} and {\it best-effort-transmit}. Next, we consider the case where energy arrivals have time-varying average in a larger time scale. We derive the optimal offline power allocation for maximum average throughput and provide an algorithm that finds the optimal power allocation.Comment: Published in IEEE PIMRC, September 201

Linear Transmission of Composite Gaussian Measurements over a Fading Channel under Delay Constraints

Delay constrained linear transmission (LT) strategies are considered for the transmission of composite Gaussian measurements over an additive white Gaussian noise fading channel under an average power constraint. If the channel state information (CSI) is known by both the encoder and decoder, the optimal LT scheme in terms of the average mean-square error distortion is characterized under a strict delay constraint, and a graphical interpretation of the optimal power allocation strategy is presented. Then, for general delay constraints, two LT strategies are proposed based on the solution to a particular multiple measurements-parallel channels scenario. It is shown that the distortion decreases as the delay constraint is relaxed, and when the delay constraint is completely removed, both strategies achieve the optimal performance under certain matching conditions. If the CSI is known only by the decoder, the optimal LT strategy is derived under a strict delay constraint. The extension to general delay constraints is elusive. As a first step towards understanding the structure of the optimal scheme in this case, it is shown that for the multiple measurementsparallel channels scenario, any LT scheme that uses only a oneto-one linear mapping between measurements and channels is suboptimal in general

Relative wage movements and the distribution of consumption

We analyze how relative wage movements across birth cohorts and education groups during the 1980s affected the distribution of household consumption. The analysis integrates the labor economics literature on time variation in the wage structure with the consumption insurance literature. In contrast to previous tests of consumption insurance, we examine the impact of systematic, publicly observable shifts in the hourly wage structure. To circumvent the extreme scarcity of longitudinal data with high quality information on both consumption and labor market outcomes, we draw upon the best available cross-sectional data sources to construct synthetic panel data on consumption, labor supply and wages. We find that low-frequency movements in the cohort-education structure of pre-tax hourly wages drove large changes in the distribution of household consumption. The results constitute a spectacular failure of the consumption insurance hypothesis, and one that is not explained by existing theories of informationally constrained optimal consumption allocations. We also develop a procedure for assessing the welfare consequences of deviations from full consumption insurance and, in particular, from the failure to insulate the consumption distribution from relative wage shifts across cohort-education groups. For a coefficient of relative risk aversion equal to two, fully insulating households from group-specific endowment variation would raise welfare by an amount equivalent to a uniform 2.7% consumption increase

Relative Wage Movements and the Distribution of Consumption

We analyze how relative wage movements across birth cohorts and education groups during the 1980s affected the distribution of household consumption. The analysis integrates the labor economics literature on time variation in the wage structure with the consumption insurance literature. In contrast to previous tests of consumption insurance, we examine the impact of systematic, publicly observable shifts in the hourly wage structure. To circumvent the extreme scarcity of longitudinal data with high quality information on both consumption and labor market outcomes, we draw upon the best available cross-sectional data sources to construct synthetic panel data on consumption, labor supply and wages. We find that low-frequency movements in the cohort-education structure of pre-tax hourly wages drove large changes in the distribution of household consumption. The results constitute a spectacular failure of the consumption insurance hypothesis, and one that is not explained by existing theories of informationally constrained optimal consumption allocations. We also develop a procedure for assessing the welfare consequences of deviations from full consumption insurance and, in particular, from the failure to insulate the consumption distribution from relative wage shifts across cohort-education groups. For a coefficient of relative risk aversion equal to two, fully insulating households from group-specific endowment variation would raise welfare by an amount equivalent to a uniform 2.7% consumption increase.

Conducting Truthful Surveys, Cheaply

We consider the problem of conducting a survey with the goal of obtaining an unbiased estimator of some population statistic when individuals have unknown costs (drawn from a known prior) for participating in the survey. Individuals must be compensated for their participation and are strategic agents, and so the payment scheme must incentivize truthful behavior. We derive optimal truthful mechanisms for this problem for the two goals of minimizing the variance of the estimator given a fixed budget, and minimizing the expected cost of the survey given a fixed variance goal