Miracle-dz/UniFAR-FTUs huggingface dataset:
The Limits of Marketplace Fee Discrimination

Platforms often use fee discrimination within their marketplace (e.g., Amazon, eBay, and Uber specify a variety of merchant fees). To better understand the impact of marketplace fee discrimination, we develop a model that allows us to determine equilibrium fee and category decisions that depend on the extent of fee discrimination available to the platform and we highlight how our fee discrimination strategies can be derived in practice using data from airbnb.com. In addition, we find that greater fee discrimination allows the platform to serve more markets in its marketplace but also increases fees in high surplus markets. However, if the platform enters into retail, then the platform reduces its fees and generates greater retail competition. These effects mitigate distortions from fee discrimination and improve welfare. In terms of policy, we show that (1) banning fee discrimination and platform entry is detrimental to welfare, (2) a vertical merger within a retail market mitigates fee distortions but is often worse than an equilibrium with platform entry into retail, and (3) taxing the platform in retail (not merchants) levels the retail playing field and can generate a Pareto improvement upon a policy that bans platform retail entry.
Africa&Apos;S Manufacturing Puzzle: Evidence from Tanzanian and Ethiopian Firms

Recent growth accelerations in Africa are characterized by increasing productivity in agriculture, a declining share of the labor force employed in agriculture and declining productivity in modern sectors such as manufacturing. To shed light on this puzzle, we disaggregate firms in the manufacturing sector by size using two newly created panels of manufacturing firms, one for Tanzania covering 2008-2016 and one for Ethiopia covering 1996-2017. Our analysis reveals a dichotomy between larger firms that exhibit superior productivity performance but do not expand employment much, and small firms that absorb employment but do not experience any productivity growth. We suggest the poor employment performance of large firms is related to use of capital-intensive techniques associated with global trends in technology. <br><br>Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at <a href="http://www.nber. org/papers/&#119;28344" TARGET="_blank">www.nber. org</a>. <br>
Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators

One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Square (OLS) estimation, a viable alternative is to use Artificial Neural Networks (ANNs) implemented in a simple structure with one input and one output layer and trained in a way such that the weights matrix corresponds to the matrix of VAR parameters. In this work, we introduce an ANN combined with SS models for the computation of GC. The ANN is trained through the Stochastic Gradient Descent L1 (SGD-L1) algorithm, and a cumulative penalty inspired from penalized regression is applied to the network weights to encourage sparsity. Simulating networks of coupled Gaussian systems, we show how the combination of ANNs and SGD-L1 allows to mitigate the strong reduction in accuracy of OLS identification in settings of low ratio between number of time series points and of VAR parameters. We also report how the performances in GC estimation are influenced by the number of iterations of gradient descent and by the learning rate used for training the ANN. We recommend using some specific combinations for these parameters to optimize the performance of GC estimation. Then, the performances of ANN and OLS are compared in terms of GC magnitude and statistical significance to highlight the potential of the new approach to reconstruct causal coupling strength and network topology even in challenging conditions of data paucity. The results highlight the importance of of a proper selection of regularization parameter which determines the degree of sparsity in the estimated network. Furthermore, we apply the two approaches to real data scenarios, to study the physiological network of brain and peripheral interactions in humans under different conditions of rest and mental stress, and the effects of the newly emerged concept of remote synchronization on the information exchanged in a ring of electronic oscillators. The results highlight how ANNs provide a mesoscopic description of the information exchanged in networks of multiple interacting physiological systems, preserving the most active causal interactions between cardiovascular, respiratory and brain systems. Moreover, ANNs can reconstruct the flow of directed information in a ring of oscillators whose statistical properties can be related to those of physiological networks.
Prudence and Information Rigidity of EBRD’s Growth Forecast: Quarter-Century Assessment

This study assesses the performance of the GDP growth forecasts by European Bank for Reconstruction and Development (EBRD) for 38 countries between 1994 and 2019. It presents the following results. First, forecast performances improve over time. Second, the projections are mostly conservative, except for some countries with optimistic next-year forecasts. Third, these forecasts are broadly rational once asymmetric loss is assumed. Fourth, the magnitude of improvement in forecast performance, conservativeness, and optimism, are likely to differ across regions, common wealth status, and income levels. Fifth, information rigidity is mostly found to be present. Sixth, there is less information rigidity in the short-term horizon in more recent years, suggesting that an improvement of the EBRD’s forecasting practice and expanded information availability in the transition economies enhance its efficiency.
European Differences in the Valuation of Earnings and Book Value: Regulation Effects or Industry Effects?

This paper uses a valuation framework for a sample of firms from four European countries (France, Germany, Netherlands, and United Kingdom) to examine how are their accounting income and book value of equity perceived by the respective capital markets after taking into account industry effects. The empirical model, based on Ohlson (1995), posits relationship between income, and book value of equity and market prices. In our tests we take into account the time series properties (linear information dynamics) of the accounting variables posited in the Ohlson model and, in a separate model, we test for the accrual adjustments in earnings. Consistently with previous researchers we find that both earnings and book value of equity have valuation implications, that there are significant country specific differences in the valuation multiples but the differences are substantially reduced when we take into account industry effects.
A Study of Q-switched Nd:YAG Laser versus Itraconazole in Management of Onychomycosis

Abstract Context: Onychomycosis (OM) accounts for 20%–40% of all nail disorders. Slow growth of nails, resistance to antifungal drugs, their side effects, and drug interactions limit treatment options. Q-switched neodymium-doped yttrium aluminum garnet (Nd:YAG) laser is approved for nail clearance of OM, however conflicting reports exist in literature about its efficacy. This study was conducted to compare the efficacy of Q-switched Nd:YAG laser. Aim: The aim of this study was to find the efficacy of Q-switched Nd:YAG laser (1064 nm) management of OM as monotherapy in comparison to itraconazole. Settings and Design: A randomized parallel group, outcome assessor trial was conducted over 18 months from July 1, 2015 to December 31, 2016, at skin center of a tertiary care hospital. Subjects and Methods: In the first group, patients of OM were administered 12 weekly sessions of the laser. Second group was administered itraconazole 200 mg twice a day for 1 week per month for the 3 months. Confirmed cases of OM, who had not received treatment 6 months before presentation, were selected and randomly allocated to two groups of 50 each. Onychomycosis severity index (OSI) and visual analog scale (VAS) score were used to assess nail involvement at the start of study, 3 months and 1 year after enrollment. Statistical Analysis: Clinical profile of patients was analyzed by chi-square test for qualitative variables. For comparison of quantitative variables, Student t test was performed. A 5% probability level was considered as statistically significant (P < 0.05). Results: VAS and OSI showed statistically significant improvement at 3 and 12 months in Group I, while resulting in faster clearance with laser; OSI was comparable in both groups at 12 months. Mycological cure was significantly higher in Group I. Both dermatophytes as well as non-dermatophytes responded well to laser treatment, whereas non-dermatophytes responded better to laser. Conclusions: Q-switched Nd:YAG laser is effective in inducing nail clearance in OM and is better than itraconazole in managing non-dermatophyte OM.
Emergency department provider in triage: assessing site‐specific rationale, operational feasibility, and financial impact

Emergency department (ED) crowding is recognized as a critical threat to patient safety, while sub‐optimal ED patient flow also contributes to reduced patient satisfaction and efficiency of care. Provider in triage (PIT) programs—which typically involve, at a minimum, a physician or advanced practice provider conducting an initial screening exam and potentially initiating treatment and diagnostic testing at the time of triage—are frequently endorsed as a mechanism to reduce ED length of stay (LOS) and therefore mitigate crowding, improve patient satisfaction, and improve ED operational and financial performance. However, the peer‐reviewed evidence regarding the impact of PIT programs on measures including ED LOS, wait times, and costs (as variously defined) is mixed. Mechanistically, PIT programs exert their effects by initiating diagnostic work‐ups earlier and, sometimes, by equipping triage providers to directly disposition patients. However, depending on local contextual factors—including the co‐existence of other front‐end interventions and delays in ED throughput not addressed by PIT—we demonstrate how these features may or may not ultimately translate into reduced ED LOS in different settings. Consequently, site‐specific analysis of the root causes of excessive ED LOS, along with mechanistic assessment of potential countermeasures, is essential for appropriate deployment and successful design of PIT programs at individual EDs. Additional motivations for implementing PIT programs may include their potential to enhance patient safety, patient satisfaction, and team dynamics. In this conceptual article, we address a gap in the literature by demonstrating the mechanisms underlying PIT program results and providing a framework for ED decision‐makers to assess the local rationale for, operational feasibility of, and financial impact of PIT programs.
Co-Created Messaging for Influenza Vaccination in a High-Risk Hispanic Community Provides Groundwork for COVID-19 Vaccine

Purpose: Influenza/pneumonia is the eighth leading cause of death in the United States. The 2020–2021 influenza season is predicted to be further impacted by COVID-19 infections. Historical data reflect disproportionate morbidity and mortality rates in the Hispanic population for influenza and COVID-19. Influenza vaccination rates remain low in the Hispanic community. We aim to improve vaccination through a community-led event, partnering with the Cristo Rey School Dallas, located in a zip code with a higher age-adjusted influenza/pneumonia mortality rate. A survey was administered to adults attending the Influenza vaccine event to understand attitudes and perceptions about influenza, vaccination, and effective messaging strategies for the campaign. Methods: Messaging was cocreated with student health ambassadors to promote immunization and delivered through trusted sources. The health department administered vaccines to individuals >age 3 at no cost. Adults were asked to complete a 19-question survey postvaccination offered in both English and Spanish. Results: Two hundred and forty-one of 394 (61.2%) participants completed the survey. Ninety-eight percent identified as Hispanic/Latino, and the majority of surveys were administered in Spanish. Among Spanish language participants, the church bulletins (57.3%) and Spanish language radio (30.5%) were reported to be most effective modes of messaging versus word of mouth (32.9%) and social media (26.3%) for English-speaking participants. Sixteen percent of participants surveyed had never received an influenza vaccine before this event. Conclusion: Cocreated messaging delivered by trusted sources in the Hispanic community led to a successful Influenza vaccine drive with the Dallas County health department.
Spontaneous anterior cervicothoracic spinal epidural hematoma extending to clivus in SARS-CoV-2 infection

Background: The treatment of spontaneous spinal epidural hematomas (SSEHs), depending on the lesion size and myeloradicular involvement, can be surgical or conservative. Here, we present a 55-year-old patient who sustained a SSEH several months following a systemic SARS-CoV-2 infection. Case Description: A 55-year-old immunocompromised female (i.e., history 17 years ago of Hodgkin’s lymphoma, nodular sclerosis variant) recently developed a SARS-CoV-2 infection treated with nonsteroidal anti-inflammatory agents. She then reported the sudden onset of cervicodorsalgia after a slight cervical flexion/extension maneuver. The brain and cervicothoracic spine MRI studies documented a clival anterior spinal epidural hematoma with maximum spinal compression at the T1-T2 level; it also extended inferiorly to the T6 level. Two weeks later, the follow-up MRI showed a remarkable reduction in the anteroposterior diameter of the hematoma that correlated with significant neurological improvement and almost complete pain regression. She was discharged after a total 15-day hospital stay, with complete symptoms relief. Conclusion: We present a 55-year-old chronically immunocompromised (i.e., due to the history of Hodgkin’s lymphoma) female who, following a SARS-CoV-2 infection, developed an anterior SSEH extending from the clivus to the T6 spinal level that spontaneously regressed without surgical intervention.
Can Market Regimes Really be Timed with Historical Volatility?

Recent research findings suggest long-term investor utility benefits through scaling expected returns by recent realized volatility. We test for utility gains to volatility timing using a utility regime-based methodology to classify investor-specific market investment regimes based solely on recent realized volatility levels. Under this framework we find limited informational content in using recent realized volatility to forecast utility regimes for the market index. To reconcile our findings we replicate work by Moreira and Muir (2017) and find that their reported Sharpe ratio gains through volatility-managing the US market factor do not appear to be statistically significant. We find that their scheme under-performs buy and hold in terms of Sharpe ratio over 30 of the 70 twenty year sub-periods in our sample (58 out of 70 for an un-leveraged investor). Furthermore, the historical out-performance of volatility management for the market index is highly sensitive to the timing of re-balancing within a month, suggesting that the strategy may not be robust to the precise timing of key market events relative to volatility changes. Strategy adopters should be aware that this timing is not guaranteed to line up favorably over future investment periods.
Solubility of swietenia mahagoni seed in supercritical carbon dioxide extraction

Swietenia mahagoni (S. mahogany) is a group of plant that is known to have an insecticidal activity as well as medicinal uses such as hypertension, diabetes and malaria. The main purpose of this research was to study the effect of temperature, pressure, and solvent flow rate on extraction yield of S. mahagoni as well as to establish the solubility data for S. mahagoni. In this study, supercritical carbon dioxide (SC-CO2) extraction was applied for extraction of S. mahagoni oil from seeds at different temperatures (40 °C to 60 °C) and pressures (15 MPa to 35 MPa). The effects of temperature and pressure on the extraction yield and solubility of oil were determined. The current results showed that an increase of temperature and pressure increased the extraction of oil. In addition, the morphological of S. mahagoni structure before and after the extraction process was observed by scanning electron microscopy (SEM). For solubility study of S. mahagoni, a dynamic method of extraction was applied and a density based-model was used in comparison with experimental solubility data. The experimental solubility data for S. mahagoni was correlated with the Chrastil model with the lowest average absolute percent deviation (AAPD) value of 0.3315 with the values of parameter k, a and b as 4.7040, -6368.4400 and -10.9353, respectively. The optimization process was conducted using a commercial response surface methodology software. Analysis of variance (ANOVA) showed that the value of R2 was 0.9391 implies that 93.91% of the total variance is explained by the model, indicating a good correlation and agreement between the experimental and the predicted values
Disclosure and Competition for Capital

Ownership segmentation in the municipal bond market gives rise to competition among local issuers for a limited supply of capital. We consider the disclosure implications of this competition for capital, using Moody’s 2010 recalibration of the municipal rating scale. The recalibration placed lowly upgraded issuers at a disadvantage relative to their highly upgraded peers within the same market segment. We develop a model in which two municipal bond issuers compete for investors’ capital by choosing bond yields. The model predicts the issuer that is disadvantaged by the recalibration is more likely to improve its disclosure to better compete with its advantaged peer if (i) the rating upgrade that its peer receives is higher and (ii) competition for capital is fiercer. Empirically, we find that the disadvantaged issuers provide more and timelier financial disclosures after the recalibration. This improvement in disclosure quality increases in the extent of the issuer’s disadvantage, arises only if we consider peers with whom the issuer directly competes for capital, and is pronounced when the local capital supply is constrained. Our analytical and empirical analyses support the idea that a competitive disadvantage in raising capital in segmented markets can motivate issuers to improve disclosure quality. This paper was accepted by Brian Bushee, accounting.
Estimating the Demand Spillover Effect of Inventory Stockouts in a Fashion Footwear Retail Setting

Problem Definition: In brick-and-mortar fashion retail stores, inventory stockouts are frequent and widespread. When a specific size of a fashion product is out-of-stock, the unmet demand might not be completely lost due to spillovers to adjacent sizes of the same product. We empirically estimate this cross-size demand spillover effect of inventory stockouts in a fashion retail setting. <br><br>Academic/Practical Relevance: Little research has been done to study consumer responses to stockouts of fashion products, partly due to researchers’ inaccessibility to proprietary data of fashion retailers. Moreover, it is challenging to estimate stockout-based substitution patterns using existing approaches due to the enormous number of stock keeping units (SKUs) and frequent stockouts in fashion retail stores. <br><br>Methodology: We obtain a large-scale data set from one of the largest sportswear retail chains in China, whose retail stores are dedicated to distributing products of a single world-renowned brand. Employing around 1.5 million granular and real-time sales and inventory records of 217 stores, 503 men’s footwear products, and 4,024 SKUs over a two-year period, we develop a difference-in-differences framework to estimate the demand spillover effect of inventory stockouts. We demonstrate the validity of this framework by conducting a pre-trend test and a placebo test. <br><br>Results: We find that on average the stockout of a men’s footwear SKU led to a 23.0% increase in the daily sales of the adjacent-larger-size SKU of the same product and a 19.8% increase in the daily sales of the adjacent-smaller-size SKU of the same product. The magnitude of the cross-size demand spillover effect is larger in regular stores than in flagship stores or stores in prominent locations, larger for casual sports shoes than for specialized sports shoes, and larger for low-price products than for high-price products. We do not find evidence that the stockout of a footwear SKU would lead to a significant change in the daily sales of the same-size SKUs of other products. <br><br>Managerial Implications: At the store level, we recommend the sales staff to encourage consumers to try adjacent larger/smaller-size SKUs when their most preferred size is out-of-stock. At the corporate level, our counterfactual analysis demonstrates that incorporating the cross-size demand spillover effect into the sportswear retail chain’s proactive transshipment decision can reduce its transshipment cost substantially and improve its profitability.
An Econometric Estimation of Post-Harvest Losses of Cut-Flowers in Punjab, Pakistan

The study was conducted to quantify the post-harvest losses (PHL) of cut-flowers at various levels of market intermediaries’ i.e. farm, commission agent, wholesale market and retail levels. Primary data were collected from district Kasur, Lahore, Sheikhupura, and Faisalabad. The respondents were selected by employing the stratified random sampling technique. SPSS was used for the descriptive statistics and multiple regression model analysis for econometric estimation. The econometric estimation revealed that variable of education, experience, floriculture area, picking method; picking time and extension services had a significant impact on losses on farm level, whereas education and infrastructure showed a significant effect on losses at a commission agent level. The determinants of PHL at the wholesale level were experience, loading method, and cold storage, transportation while education, unsold quantity, retailer type, kind of shop and storage place had a significant effect on losses at the retailer level. Proper training and scientific knowledge should be given to traders regarding storage, grading, handling, displaying and processing of flowers. The study suggests adopting a scientific approach to minimize these losses.