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Book part
Publication date: 5 April 2024

Feng Yao, Qinling Lu, Yiguo Sun and Junsen Zhang

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…

Abstract

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.

Details

Essays in Honor of Subal Kumbhakar
Type: Book
ISBN: 978-1-83797-874-8

Keywords

Article
Publication date: 3 April 2023

Oscar Valdemar De la Torre-Torres, María Isabel Martínez Torre-Enciso, María de la Cruz Del Río-Rama and José Álvarez-García

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…

Abstract

Purpose

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.

Design/methodology/approach

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).

Findings

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.

Practical implications

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.

Originality/value

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

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