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The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

Biotech companies stand as key actors in pharmaceutical innovation. The high risk and long timelines inherent with their R&D investments might hinder their access to funding, potentially stifling innovation. This study aims to explore into the appeal of biotech companies to capital market investors, whose financial backing could bolster the growth of the biotechnology sector.

This paper uses a dataset of 774 US publicly listed biotech firms to investigate their risk and return characteristics by comparing them to pharmaceutical firms and a sample of matched non-biotech R&D-intensive firms over the sample period 1980–2021. Tests show that the conclusions remain consistent across diverse methodological approaches.

The paper shows that biotech companies are riskier than the average firm in the market index but outperform on a risk-adjusted basis both the market and a matched group of R&D-intensive firms. This is particularly true for large capitalization biotech, which is also shown to provide a diversification benefit by reducing the downside risk in past crisis periods.

This paper provides insight relevant to the current debate about the overall performance of the biotech industry in terms of policy changes and their impact on small, early-stage biotech firms. While small and early-stage biotech firms are playing an increasing role in scientific innovation, this study confirms their greater vulnerability to financial risks and the importance of access to capital markets in enabling those companies to survive and evolve into larger biotech.

In this paper, the authors tested if promoting the workforce's happiness (through high performance work policies or HPWP) and well-being in European Public companies relates to their profitability (return on equity, ROE), market risk (beta) and stock price return. Also, the authors tested if investors have a performance benefit if they buy a portfolio screened with companies with HPWP.

The authors proxied the quality of the HPWP efforts in the first method with the Refinitiv workforce score. They used this data in an unbalanced panel of eastern, western, northern and southern Europe companies from 2011 to 2022. The panel data also included the ROE, the market risk (beta) and the stock price return of these companies. The authors estimated the corresponding regressions with the panel data and tested the relationship between the workforce score and these three variables. In a second method, they simulated the weekly performance of a portfolio that invested only in European companies with high standards in their HPWP and compared its performance against a conventional market portfolio (with no HPWP screening).

In the first method, the authors found no significant relationship between the workforce score and the ROE, beta, or stock price return in the panel regression, controlling for random effects. In the second one, they found no over or underperformance in the HPWP portfolio against the European market one in the second method.

The results suggest that there is no risk or cost for European Public companies and investors alike if they promote, with better HPWP, the happiness and well-being of their workforce. The findings suggest that if European companies promote HPWP, there will be no adverse impact on their profits, market risk, or stock price performance. Also, investors will not lose performance (against a conventional market portfolio) if they screen their portfolios with this type of workforce-friendly companies.

Increase the scarce literature on the test of the workforce score with company profitability (ROE), stock market price variation and stock market risk level.

Leveraging information technology (IT) to improve the treatment and support of patients is a widely studied topic in healthcare. For chronic diseases, such as diabetes, the use of information technology is even more important since its effect extends from a clinic environment to patients’ daily life. The purpose of this paper is to investigate the impacts of one widely adopted information technology, the mobile phone, on diabetes treatment, specifically on the complicated process of patients’ health, emotions and compliance.

We leverage a unique longitudinal dataset on diabetes patients’ health status in rural areas of China to study the problem. We also cross-link the dataset with mobile carrier data to further differentiate mobile phone use to phone calls and network use. To address the endogeneity concerns, we apply PSM and a series of instrument variables.

We identify clear evidence that mobile phone use can significantly improve patients’ emotions and compliance, where the effect is generally larger on patients in worse health conditions. While mobile phone calls clearly benefit diabetes patients, we do notice that mobile phone network use has a negative moderating effect with patients’ health condition on improving compliance.

This study not only enriches our theoretical understanding of the role of mobile phones in diabetes management, it also shows the economic benefit of promoting patients’ use of mobile phones, which should be considered by medical care providers and medical policymakers.