Income taxes as reciprocal tariffs

Tariff ; Taxation

Income taxes as reciprocal tariffs

This article shows the equivalence between tariffs on international trade and income taxation. Traditionally, income taxes have been seen as lowering society's output through the household's labor-leisure trade-off. Income taxes also reduce the degree to which individuals specialize in market activity, which is similar to the way countries respond to tariffs in international trade. Income taxes discourage individuals from specializing in activities that reflect their comparative advantage. In so doing, income taxes may have their most distorting effects, not by encouraging individuals to work less but by causing them to spend more time working at endeavors for which their talent is limited. Using a general model of interpersonal exchange, the authors demonstrate parallels between income taxes and tariffs. Over a range of income taxes, raising taxes can benefit large groups of similarly skilled individuals and hurt small groups. As in tariff theory, the costs of income taxes are small only if they succeed in raising revenue. Thus, it is very costly for an economy to be on the downward portion of its tax revenue (Laffer) curve. The more heterogeneous the society, the higher the income tax rate that will maximize tax revenues. By overlooking the effects of heterogeneity in the workforce and the potential for workers to flee to home production, policymakers may under- or overestimate the effects of income taxes on various sectors of the economy and tax with unintended consequences.Income tax ; Tariff ; Taxation

Pathwise super-replication via Vovk's outer measure

Since Hobson's seminal paper [D. Hobson: Robust hedging of the lookback option. In: Finance Stoch. (1998)] the connection between model-independent pricing and the Skorokhod embedding problem has been a driving force in robust finance. We establish a general pricing-hedging duality for financial derivatives which are susceptible to the Skorokhod approach. Using Vovk's approach to mathematical finance we derive a model-independent super-replication theorem in continuous time, given information on finitely many marginals. Our result covers a broad range of exotic derivatives, including lookback options, discretely monitored Asian options, and options on realized variance.Comment: 18 page

Dead-time effects on the voltage spectrum of a PWM inverter

An inverter converts a direct-current power supply to an alternating-current power supply. This con- version is achieved by switching the output between the inputs at high frequency. The resulting output voltage may be described by a high-frequency train of variable-width pulses. Pulse widths are slowly modulated so that this output waveform contains a prescribed low-frequency component, which may then be isolated by an appropriate filtering regime. Techniques for determining the full harmonic spec- trum of input and output voltages and currents are well established, at least for an idealised mathematical model of the inverter. However, this model assumes that changes of inverter configuration can be ef- fected instantaneously, which is not quite the case in practice. In fact, a small amount of dead time must be incorporated into switching regimes in order to avoid short circuits of the input. Although dead time is an important feature of real power conversion devices, its effects on output voltage spectra have not previously been fully determined (except by imposing rather restrictive approximations). This situation is remedied in the present paper, in which we present closed-form expressions for the coefficients of the harmonic spectrum, corroborated by simulations

Toward Automation of the Supine Pressor Test for Preeclampsia

Preeclampsia leads to increased risk of morbidity and mortality for both mother and fetus. Most previous studies have largely neglected mechanical compression of the left renal vein by the gravid uterus as a potential mechanism. In this study, we first used a murine model to investigate the pathophysiology of left renal vein constriction. The results indicate that prolonged renal vein stenosis after 14 days can cause renal necrosis and an increase in blood pressure (BP) of roughly 30 mmHg. The second part of this study aimed to automate a diagnostic tool, known as the supine pressor test (SPT), to enable pregnant women to assess their preeclampsia development risk. A positive SPT has been previously defined as an increase of at least 20 mmHg in diastolic BP when switching between left lateral recumbent and supine positions. The results from this study established a baseline BP increase between the two body positions in nonpregnant women and demonstrated the feasibility of an autonomous SPT in pregnant women. Our results demonstrate that there is a baseline increase in BP of roughly 10-14 mmHg and that pregnant women can autonomously perform the SPT. Overall, this work in both rodents and humans suggests that (1) stenosis of the left renal vein in mice leads to elevation in BP and acute renal failure, (2) nonpregnant women experience a baseline increase in BP when they shift from left lateral recumbent to supine position, and (3) the SPT can be automated and used autonomously

Critical role for p53-serine 15 phosphorylation in stimulating transactivation at p53-responsive promoters

The p53 tumour suppressor is induced by various stress stimuli and coordinates an adaptive gene expression programme leading to growth arrest or cell death. Some stimuli, such as DNA damage, lead to rapid and substantial multisite phosphorylation of p53, nucleated initially through phosphorylation of serine 15. Other stimuli, such as hyper-proliferation, do not stimulate p53-phosphorylation, raising questions regarding the physiological role for phosphorylation. Here, we show that a basal level of Ser15 phosphorylation occurs in both unstimulated cells and cells stimulated pharmacologically to induce p53. p53 in which Ser15 is substituted by alanine (S15A) fails to mediate p53-dependent transcription or growth arrest but can be rescued by substitution with aspartate (S15D: a phospho-mimic). Chromatin immunoprecipitation (ChIP) analyses show that, while wt- and S15A-p53 are detectable on the CDKN1A (p21) promoter (as a representative p53-responsive promoter), S15A-p53 does not stimulate histone acetylation (a measure of chromatin relaxation), nor is its recruitment stimulated, in response to a DNA damage or pharmacological stimulus. These data demonstrate that Ser15 phosphorylation is required for p53 function in the physiological context of p53-responsive promoters and suggest a key and possibly universal role even for low levels of this modification in promoting p53-transcription function

Long term (5 Year) safety of bronchial thermoplasty: Asthma Intervention Research (AIR) trial

<b>Background:</b> Bronchial thermoplasty (BT) is a bronchoscopic procedure that improves asthma control by reducing excess airway smooth muscle. Treated patients have been followed out to 5 years to evaluate long-term safety of this procedure. <br></br> <br></br> <b>Methods:</b> Patients enrolled in the Asthma Intervention Research Trial were on inhaled corticosteroids ≥200 μg beclomethasone or equivalent + long-acting-beta2-agonists and demonstrated worsening of asthma on long-acting-β2-agonist withdrawal. Following initial evaluation at 1 year, subjects were invited to participate in a 4 year safety study. Adverse events (AEs) and spirometry data were used to assess long-term safety out to 5 years post-BT. <br></br> <br></br> <b>Results:</b> 45 of 52 treated and 24 of 49 control group subjects participated in long-term follow-up of 5 years and 3 years respectively. The rate of respiratory adverse events (AEs/subject) was stable in years 2 to 5 following BT (1.2, 1.3, 1.2, and 1.1, respectively,). There was no increase in hospitalizations or emergency room visits for respiratory symptoms in Years 2, 3, 4, and 5 compared to Year 1. The FVC and FEV1 values showed no deterioration over the 5 year period in the BT group. Similar results were obtained for the Control group. <br></br><br></br> <b>Conclusions:</b> The absence of clinical complications (based on AE reporting) and the maintenance of stable lung function (no deterioration of FVC and FEV1) over a 5-year period post-BT in this group of patients with moderate to severe asthma support the long-term safety of the procedure out to 5 years

Minnorm training: an algorithm for training over-parameterized deep neural networks

In this work, we propose a new training method for finding minimum weight norm solutions in over-parameterized neural networks (NNs). This method seeks to improve training speed and generalization performance by framing NN training as a constrained optimization problem wherein the sum of the norm of the weights in each layer of the network is minimized, under the constraint of exactly fitting training data. It draws inspiration from support vector machines (SVMs), which are able to generalize well, despite often having an infinite number of free parameters in their primal form, and from recent theoretical generalization bounds on NNs which suggest that lower norm solutions generalize better. To solve this constrained optimization problem, our method employs Lagrange multipliers that act as integrators of error over training and identify `support vector'-like examples. The method can be implemented as a wrapper around gradient based methods and uses standard back-propagation of gradients from the NN for both regression and classification versions of the algorithm. We provide theoretical justifications for the effectiveness of this algorithm in comparison to early stopping and $L_2$-regularization using simple, analytically tractable settings. In particular, we show faster convergence to the max-margin hyperplane in a shallow network (compared to vanilla gradient descent); faster convergence to the minimum-norm solution in a linear chain (compared to $L_2$-regularization); and initialization-independent generalization performance in a deep linear network. Finally, using the MNIST dataset, we demonstrate that this algorithm can boost test accuracy and identify difficult examples in real-world datasets