Testable implications of forecast optimality

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted on the assumption of mean squared error loss under which forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. This paper considers properties of optimal forecasts under general loss functions and establishes new testable implications of forecast optimality. These hold when the forecaster’s loss function is unknown but testable restrictions can be imposed on the data generating process, trading off conditions on the data generating process against conditions on the loss function. Finally, we propose flexible parametric estimation of the forecaster’s loss function, and obtain a test of forecast optimality via a test of over-identifying restrictions

Can Affirmative Action be Cost-Effective? An Experimental Examination of Price-Preference Auctions

Affirmative action, auctions, experiments

Symplectic Maps from Cluster Algebras

We consider nonlinear recurrences generated from the iteration of maps that arise from cluster algebras. More precisely, starting from a skew-symmetric integer matrix, or its corresponding quiver, one can define a set of mutation operations, as well as a set of associated cluster mutations that are applied to a set of affine coordinates (the cluster variables). Fordy and Marsh recently provided a complete classification of all such quivers that have a certain periodicity property under sequences of mutations. This periodicity implies that a suitable sequence of cluster mutations is precisely equivalent to iteration of a nonlinear recurrence relation. Here we explain briefly how to introduce a symplectic structure in this setting, which is preserved by a corresponding birational map (possibly on a space of lower dimension). We give examples of both integrable and non-integrable maps that arise from this construction. We use algebraic entropy as an approach to classifying integrable cases. The degrees of the iterates satisfy a tropical version of the map

Reversal of cardiac dysfunction by selective ET-A receptor antagonism

1. The effectiveness of a selective endothelin receptor-A (ET-A) antagonist, A-127722 (approximately 10 mg kg-1 day-1 as 200 mg kg-1 powdered food), to reverse existing cardiac remodelling and prevent further remodelling was tested in deoxycorticosterone acetate (DOCA)-salt hypertensive rats. 2. Uninephrectomised rats (UNX) administered DOCA (25mg every 4th day sc) and 1% NaCl in drinking water for 28 days developed hypertension (systolic BP: UNX 128 6, DOCA-salt 182 5* mmHg; *P<0.05 vs UNX), left ventricular hypertrophy (UNX 1.99 0.06, DOCA-salt 3.30 0.08* mg/kg body wt), decreased left ventricular internal diameter (UNX 6.69 0.18, DOCA-salt 5.51 0.37* mm), an increased left ventricular monocyte/macrophage infiltration together with an increased interstitial collagen from 2.7 0.3 to 11.7 1.3%, increased passive diastolic stiffness (UNX 21.1 0.5, DOCA-salt 30.1 1.3*), prolongation of the action potential duration at 20% and 90% of repolarization (APD20 - UNX 6.8 1.1, DOCA-salt 10.1 1.5* msec; APD90 - UNX 34.4 3.5, DOCA-salt 64.3 10.4* msec) and vascular dysfunction (2.6 fold decrease in maximal contractile response to noradrenaline, 3.5 fold decrease in maximal relaxation response to acetylcholine). 3. Administration of A-127722 for 14 days starting 14 days after surgery attenuated the increases in systolic blood pressure (150 6** mmHg, **P<0.05 vs DOCA-salt), left ventricular wet weight (2.65 0.06** mg/kg body wt) and internal diameter (6.39 0.31** mm), prevented left ventricular monocyte/macrophage accumulation, attenuated the increased left ventricular interstitial collagen (7.6 1.3%**), reversed the increased passive diastolic stiffness (22.1 1.2**), attenuated the action potential duration prolongation (APD20 - 7.6 1.4**, APD90 - 41.5 6.9** msec) and normalized changes in vascular function. 4. ET-A receptor antagonism both reverses and prevents the cardiac and vascular remodelling in DOCA-salt hypertension and improves cardiovascular function

Testable Implications of Forecast Optimality

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted on the assumption of mean squared error loss under which forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. This paper considers properties of optimal forecasts under general loss functions and establishes new testable implications of forecast optimality. These hold when the forecaster's loss function is unknown but testable restrictions can be imposed on the data generating process, trading off conditions on the data generating process against conditions on the loss function. Finally, we propose flexible parametric estimation of the forecaster's loss function, and obtain a test of forecast optimality via a test of over-identifying restrictions.forecast evaluation, loss function, rationality tests

Properties of Optimal Forecasts

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors should be serially uncorrelated at the single period horizon with increasing variance as the forecast horizon grows. Using analytical results, we show in this paper that all the standard properties of optimal forecasts can be invalid under asymmetric loss and nonlinear data generating processes and thus may be very misleading as a benchmark for an optimal forecast. Our theoretical results suggest that many of the conclusions in the empirical literature concerning suboptimality of forecasts could be premature. We extend the properties that an optimal forecast should have to a more general setting than previously considered in the literature. We also present results on forecast error properties that may be tested when the forecaster's loss function is unknown, and introduce a change of measure, following which the optimum forecast errors for general loss functions have the same properties as optimum errors under MSE lossforecast evaluation, loss function, rationality, efficient markets