Sparse HP filter: Finding kinks in the COVID-19 contact rate.

In this paper, we estimate the time-varying COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model. Our measurement of the contact rate is constructed using data on actively infected, recovered and deceased cases. We propose a new trend filtering method that is a variant of the Hodrick-Prescott (HP) filter, constrained by the number of possible kinks. We term it the sparse HP filter and apply it to daily data from five countries: Canada, China, South Korea, the UK and the US. Our new method yields the kinks that are well aligned with actual events in each country. We find that the sparse HP filter provides a fewer kinks than the ℓ 1 trend filter, while both methods fitting data equally well. Theoretically, we establish risk consistency of both the sparse HP and ℓ 1 trend filters. Ultimately, we propose to use time-varying contact growth rates to document and monitor outbreaks of COVID-19.

DESPERATE TIMES CALL FOR DESPERATE MEASURES: GOVERNMENT SPENDING MULTIPLIERS IN HARD TIMES.

We investigate state-dependent effects of fiscal multipliers and allow for endogenous sample splitting to determine whether the U.S. economy is in a slack state. When the endogenized slack state is estimated as the period of the unemployment rate higher than about 12%, the estimated cumulative multipliers are significantly larger during slack periods than nonslack periods and are above unity. We also examine the possibility of time-varying regimes of slackness and find that our empirical results are robust under a more flexible framework. Our estimation results point out the importance of the heterogenous effects of fiscal policy and shed light on the prospect of fiscal policy in response to economic shocks from the current COVID-19 pandemic. (JEL C32, E62, H20, H62).

Testing for a Debt-Threshold Effect on Output Growth.

Using the Reinhart-Rogoff dataset, we find a debt threshold not around 90 per cent but around 30 per cent, above which the median real gross domestic product (GDP) growth falls abruptly. Our work is the first to formally test for threshold effects in the relationship between public debt and median real GDP growth. The null hypothesis of no threshold effect is rejected at the 5 per cent significance level for most cases. While we find no evidence of a threshold around 90 per cent, our findings from the post-war sample suggest that the debt threshold for economic growth may exist around a relatively small debt-to-GDP ratio of 30 per cent. Furthermore, countries with debt-to-GDP ratios above 30 per cent have GDP growth that is 1 percentage point lower at the median.

The lasso for high dimensional regression with a possible change point.

We consider a high dimensional regression model with a possible change point due to a covariate threshold and develop the lasso estimator of regression coefficients as well as the threshold parameter. Our lasso estimator not only selects covariates but also selects a model between linear and threshold regression models. Under a sparsity assumption, we derive non-asymptotic oracle inequalities for both the prediction risk and the l1-estimation loss for regression coefficients. Since the lasso estimator selects variables simultaneously, we show that oracle inequalities can be established without pretesting the existence of the threshold effect. Furthermore, we establish conditions under which the estimation error of the unknown threshold parameter can be bounded by a factor that is nearly n-1 even when the number of regressors can be much larger than the sample size n. We illustrate the usefulness of our proposed estimation method via Monte Carlo simulations and an application to real data.

Floating electrode transistor based on purified semiconducting carbon nanotubes for high source-drain voltage operation.

We report floating-electrode-based thin-film transistors (F-TFTs) based on a purified semiconducting single-walled carbon nanotube (swCNT) network for a high source-drain voltage operation. At a high source-drain voltage, a conventional swCNT-TFT exhibited poor transistor performance with a small on-off ratio, which was attributed to the reduced Schottky barrier modulation at a large bias. In the F-TFT device, an swCNT network channel was separated into a number of channels connected by floating electrodes. The F-TFTs exhibited a much higher on-off ratio than a conventional swCNT-TFT with a single channel. This work should provide an important guideline in designing swCNT-TFTs for high voltage applications such as displays.

TRPV1 recapitulates native capsaicin receptor in sensory neurons in association with Fas-associated factor 1.

TRPV1, a cloned capsaicin receptor, is a molecular sensor for detecting adverse stimuli and a key element for inflammatory nociception and represents biophysical properties of native channel. However, there seems to be a marked difference between TRPV1 and native capsaicin receptors in the pharmacological response profiles to vanilloids or acid. One plausible explanation for this overt discrepancy is the presence of regulatory proteins associated with TRPV1. Here, we identify Fas-associated factor 1 (FAF1) as a regulatory factor, which is coexpressed with and binds to TRPV1 in sensory neurons. When expressed heterologously, FAF1 reduces the responses of TRPV1 to capsaicin, acid, and heat, to the pharmacological level of native capsaicin receptor in sensory neurons. Furthermore, silencing FAF1 by RNA interference augments capsaicin-sensitive current in native sensory neurons. We therefore conclude that FAF1 forms an integral component of the vanilloid receptor complex and that it constitutively modulates the sensitivity of TRPV1 to various noxious stimuli in sensory neurons.