Alternative Asymptotics and the Partially Linear Model with Many Regressors

Non-standard distributional approximations have received considerable attention in recent years. They often provide more accurate approximations in small samples, and theoretical improvements in some cases. This paper shows that the seemingly unrelated "many instruments asymptotics" and "small bandwidth asymptotics" share a common structure, where the object determining the limiting distribution is a V-statistic with a remainder that is an asymptotically normal degenerate U-statistic. We illustrate how this general structure can be used to derive new results by obtaining a new asymptotic distribution of a series estimator of the partially linear model when the number of terms in the series approximation possibly grows as fast as the sample size, which we call "many terms asymptotics"

A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix

This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.

Fairness as “appropriate impartiality” and the problem of the self-serving bias

Garrett Cullity contends that fairness is appropriate impartiality (See Cullity (2004) Chapters 8 and 10 and Cullity (2008)). Cullity deploys his account of fairness as a means of limiting the extreme moral demand to make sacrifices in order to aid others that was posed by Peter Singer in his seminal article ‘Famine, Affluence and Morality’. My paper is founded upon the combination of (1) the observation that the idea that fairness consists in appropriate impartiality is very vague and (2) the fact that psychological studies show the self-serving bias is especially likely to infect one’s judgements when the ideas involved are vague. I argue that Cullity’s solution to extreme moral demandingness is threatened by these findings. I then comment on whether some other theories of fairness are vulnerable to the same objection

Combination Forecasts of Bond and Stock Returns: An Asset Allocation Perspective

We investigate the out-of-sample forecasting ability of the HML, SMB, momentum, short-term and long-term reversal factors along with their size and value decompositions on U.S. bond and stock returns for a variety of horizons ranging from the short run (1 month) to the long run (2 years). Our findings suggest that these factors contain significantly more information for future bond and stock market returns than the typically employed financial variables. Combination of forecasts of the empirical factors turns out to be particularly successful, especially from an an asset allocation perspective. Similar findings pertain to the European and Japanese markets

Choice-Based Demand Management and Vehicle Routing in E-Fulfillment

Attended home delivery services face the challenge of providing narrow delivery time slots to ensure customer satisfaction, while keeping the significant delivery costs under control. To that end, a firm can try to influence customers when they are booking their delivery time slot so as to steer them toward choosing slots that are expected to result in cost-effective schedules. We estimate a multinomial logit customer choice model from historic booking data and demonstrate that this can be calibrated well on a genuine e-grocer data set. We propose dynamic pricing policies based on this choice model to determine which and how much incentive (discount or charge) to offer for each time slot at the time a customer intends to make a booking. A crucial role in these dynamic pricing problems is played by the delivery cost, which is also estimated dynamically. We show in a simulation study based on real data that anticipating the likely future delivery cost of an additional order in a given location can lead to significantly increased profit as compared with current industry practice

Semiparametric theory and empirical processes in causal inference

In this paper we review important aspects of semiparametric theory and empirical processes that arise in causal inference problems. We begin with a brief introduction to the general problem of causal inference, and go on to discuss estimation and inference for causal effects under semiparametric models, which allow parts of the data-generating process to be unrestricted if they are not of particular interest (i.e., nuisance functions). These models are very useful in causal problems because the outcome process is often complex and difficult to model, and there may only be information available about the treatment process (at best). Semiparametric theory gives a framework for benchmarking efficiency and constructing estimators in such settings. In the second part of the paper we discuss empirical process theory, which provides powerful tools for understanding the asymptotic behavior of semiparametric estimators that depend on flexible nonparametric estimators of nuisance functions. These tools are crucial for incorporating machine learning and other modern methods into causal inference analyses. We conclude by examining related extensions and future directions for work in semiparametric causal inference

On the Behaviour of Phillips-Perron Tests in the Presence of Persistent Cycles

In this paper, we analyse the impact of persistent cycles on the well-known semi-parametric unit root tests of Phillips and Perron (1988, Biometrika, Vol. 75, pp. 335-346). It is shown, both analytically and through Monte Carlo simulations, that the presence of complex (near) unit roots can severely bias the size properties of these tests. Given the popularity of these tests with applied researchers and their routine presence in most econometric software packages, the results presented in this paper suggest that practitioners should treat the outcomes of these tests with some caution when applied to data which display a strong cyclical component

Survey and scoping of wildcat priority areas

This report summarises the findings of three complementary projects commissioned by SNH to inform the selection of Priority Areas for wildcat conservation; as proposed in the Scottish Wildcat Conservation Action Plan 2013. The scoping projects combined field surveys, taxonomic and genetic assessments, population modelling and a questionnaire survey of public attitudes to wildcat conservation measures. The report makes a recommendations for six wildcat Priority Areas from the nine areas pre-selected by SNH for survey. The sites recommended as Priority Areas all had evidence of cats that were classified as wildcats based on their appearance. However, domestic cats or hybrids (between domestic cats and wildcats) were also found, highlighting the need for conservation actions to reduce the risks they pose to wildcats from hybridisation and disease

A STUDY OF THE UTILIZATION OF PANEL METHOD FOR LOW ASPECT RATIO WING ANALYSIS

This study demonstrates the applicability of using a modified application strategy of panel method to analyze low aspect ratio wings at preliminary design phases. Conventional panel methods fail to capture the leading edge vortex (LEV) that is shed by wings with low aspect ratios, typically below 2 depending on planform. This aerodynamic phenomenon contributes to a significant amount of the lift of these wings and the result is a drastic underestimation of the lift characteristics when analyzed by conventional panel method. To capture the effect of the leading edge vortex, a panel method code was used with an extended definition of the Kutta condition along portions of the leading edge inducing a vortex to shed from the leading edge and flow aft just inside the leading edge. To validate that this method, it was applied to 2 elliptical planforms with constant thickness where experimental force balance data was available. Additionally, the same 2 wings were analyzed using a finite volume solver to compare pressure distributions and to demonstrate the difference in magnitude of solution times. For comparison purposes, the resulting forces and moments from both computational methods and experimental testing were plotted over a range of angles of attack. Overall, the results demonstrate that a modified panel method could be used during the preliminary design phases for low aspect ratio wings. The panel method can reasonably model the lift and induced drag characteristics of low aspect ratio wings. This method loses applicability beyond the stall point where the leading edge vortex breaks down and oversimplifies pitching moment relation to angle of attack. Additionally, when compared to finite volume solutions of the same scenario, the panel method provided a result 20 to 30 times faster than the finite volume solutions. With this in mind, the modified panel method application strategy lends itself to preliminary design phases of low aspect ratio wings where the level of detail does not warrant finite volume analysis and solution speed has higher priority