Identifying Present Bias from the Timing of Choices

A (partially naïve) quasi-hyperbolic discounter repeatedly chooses whether to complete a task. Her net benefits of task completion are drawn independently between periods from a time-invariant distribution. We show that the probability of completing the task conditional on not having done so earlier increases towards the deadline. Conversely, we establish nonidentifiability by proving that for any time-preference parameters and any dataset with such (weakly increasing) task-completion probabilities, there exists a stationary payoff distribution that rationalizes the agent’s behavior if she is either sophisticated or fully naïve. Additionally, we provide sharp partial identification for the case of observable continuation values. (JEL C14, D11, D15, D90, D91)

Bounding Infection Prevalence by Bounding Selectivity and Accuracy of Tests: With Application to Early COVID-19

I propose novel partial identification bounds on infection prevalence from information on test rate and test yield. The approach utilizes user-specified bounds on (i) test accuracy and (ii) the extent to which tests are targeted, formalized as restriction on the effect of true infection status on the odds ratio of getting tested and thereby embeddable in logit specifications. The motivating application is to the COVID-19 pandemic but the strategy may also be useful elsewhere. Evaluated on data from the pandemic’s early stage, even the weakest of the novel bounds are reasonably informative. Notably, and in contrast to speculations that were widely reported at the time, they place the infection fatality rate for Italy well above the one of influenza by mid-April.

Why Does Mary Weep? Emotion and Gender in Advent Lines 164–213 (Advent Lyric VII)

This article re-reads Lyric VII of the poem Advent, the dialogue of Mary and Joseph. The division of speeches in this lyric has been debated, largely on grounds of the plausibility of the emotions that are apparently expressed by the characters, but there are in fact clear pragmatic grounds for seeing only three speeches in the poem. The emotional expression in these speeches should not be seen in terms of character psychology, but rather the establishment and negotiation of relational stances. In her first speech, Mary expresses bitter grief and draws attention to her weeping, which is because of the insults and gossip she is suffering; the accent on shame and reputation is a distinctive emphasis in the poet’s treatment of the material. Her display of grief elicits Joseph’s response and paves the way to resolution in Mary’s final speech. Mary’s tears are gendered, but not so much because tears are inherently feminine as because they are associated with petition and dependence, and reflect Mary’s social subordination to her betrothed spouse. Lyric VII prompts its audience to a partial identification with Mary and reflection on their need for God and his mercy; such identification would work differently for female and male readers.

Endonuclease-based genotyping of the RBM, a first-line method for the surveillance of emergence or evolution of SARS-CoV-2 Variants.

Since the beginning of the Covid-19 pandemics, variants have emerged. Whereas most of them have no to limited selective advantage, some display increased transmissibility and/or resistance to immune response. To date, most of the mutations involved in the functional adaptation are found in the Receptor Binding Module (RBM), close to the interface with the human receptor ACE2. In this study, we thus developed and validated a fast and simple molecular assay allowing the detection and partial identification of the mutations in the RBM coding sequence. After the amplification of the region of interest, the amplicon is heat-denatured and hybridized with an amplicon of reference. The presence of a mutation in the heteroduplex can be cleaved by a mismatch-specific endonuclease and the cleavage pattern is analysed by capillary electrophoresis. The approach was first validated on viral RNA purified different SARS-CoV-2 variants produced in the lab before being implemented for clinical samples. The results highlighted the performance of the assay for the detection of mutations in the RBM from clinical samples. The procedure can be easily set up for high throughput identification of the presence of mutations and serve as a first-line screening to select the samples for full genome sequencing.

CONSTRAINT QUALIFICATIONS IN PARTIAL IDENTIFICATION

The literature on stochastic programming typically restricts attention to problems that fulfill constraint qualifications. The literature on estimation and inference under partial identification frequently restricts the geometry of identified sets with diverse high-level assumptions. These superficially appear to be different approaches to closely related problems. We extensively analyze their relation. Among other things, we show that for partial identification through pure moment inequalities, numerous assumptions from the literature essentially coincide with the Mangasarian–Fromowitz constraint qualification. This clarifies the relation between well-known contributions, including within econometrics, and elucidates stringency, as well as ease of verification, of some high-level assumptions in seminal papers.