Can urban coffee consumption help predict US inflation?

Motivated by the importance of coffee to Americans and the significance of the coffee subsector to the US economy, we pursue three notable innovations. First, we augment the traditional Phillips curve model with the coffee price as a predictor, and show that the resulting model outperforms the traditional variant in both in-sample and out-of-sample predictability of US inflation. Second, we demonstrate the need to account for the inherent statistical features of predictors such as persistence, endogeneity, and conditional heteroskedasticity effects when dealing with US inflation. Consequently, we offer robust illustrations to show that the choice of estimator matters for improved US inflation forecasts. Third, the proposed augmented Phillips curve also outperforms time series models such as autoregressive integrated moving average and the fractionally integrated version for both in-sample and out-of-sample forecasts. Our results show that augmenting the traditional Phillips curve with the urban coffee price will produce better forecast results for US inflation only when the statistical effects are captured in the estimation process. Our results are robust to alternative measures of inflation, different data frequencies, higher order moments, multiple data samples and multiple forecast horizons

An in vivo model for postinflammatory hyperpigmentation: an analysis of histological, spectroscopic, colorimetric and clinical traits

BACKGROUND: Acne vulgaris is a common condition that occurs in all skin types. Postinflammatory hyperpigmentation (PIH) is often associated with acne in patients of darker skin types, making it a common complaint in dermatology offices. Despite this, there is limited understanding of and effective treatment options for PIH. OBJECTIVES: The study objective was to validate an in vivo model for PIH and to compare the clinical, histological and spectroscopic characteristics of artificially induced PIH and acne-induced PIH. METHODS: A nonblinded, nonrandomized pilot study was performed. Thirty subjects served as their own control in which four sites treated with 35% trichloroacetic acid (TCA) solution and four truncal acne pustules were followed for 8 weeks and were evaluated clinically and histologically, and by colorimetry and spectroscopy. RESULTS: The initial phases of inflammation between TCA- and acne-induced PIH differ. However, clinical evaluations were similar on and after day 14. Acne- and TCA-induced lesions were clinically, histologically and spectroscopically indistinguishable at day 28. CONCLUSIONS: Clinical, spectroscopic and histological similarities of acne-induced and TCA-induced PIH at day 28 suggest that TCA-induced PIH can be a reproducible model for the study of acne-induced PIH

Does COVID

This paper aims to investigate whether COVID-19 pandemic causes the spot electricity price discovery of the Indian electricity market. To do so, we use the average daily spot electricity price data for five regions of the Indian electricity market (North, East, West, South, and North-East). The data is considered from March 15, 2020 to May 02, 2020. The results obtained from cross-sectional augmented Im, Pesaran and Shin (CIPS) unit root test show the stationary of spot electricity price and COVID-19 at the level. Additionally, we use the Dumitrescu–Hurlin (DH) panel causality test to examine the causality between spot electricity price and COVID-19. The results reveal the unidirectional causality which is running from COVID-19 to the spot electricity price discovery but no other way around. Our findings suggests to the policymakers that across different regions of India (North, East, West, South, and North-East), the ongoing coronavirus outbreak will further disrupt the electricity market