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We consider a semiparametric panel stochastic frontier model where one-sided firm effects representing inefficiencies are correlated with the regressors. A form of the Chamberlain-Mundlak device is used to relate the logarithm of the effects to the regressors resulting in a lognormal distribution for the effects. The function describing the technology is modeled nonparametrically using penalized splines. Both Bayesian and non-Bayesian approaches to estimation are considered, with an emphasis on Bayesian estimation. A Monte Carlo experiment is used to investigate the consequences of ignoring correlation between the effects and the regressors, and choosing the wrong functional form for the technology.

Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated. Recent research has seen a renewed interest in imposing constraints in nonparametric regression. We survey the available methods in the literature, discuss the challenges that present themselves when empirically implementing these methods, and extend an existing method to handle general nonlinear constraints. A heuristic discussion on the empirical implementation for methods that use sequential quadratic programming is provided for the reader, and simulated and empirical evidence on the distinction between constrained and unconstrained nonparametric regression surfaces is covered.

This paper aims to examine the different impacts of six variables on firm technological innovation performance in different high-tech industries in China. Through a comparative analysis of data about growth enterprises market board (GEM)-listed companies, this study attempts to get some conclusions, to help firms in different high-tech industries use resources more rationally and to improve technological innovation performance more effectively.

This paper constructs semi-parametric models based on the relevant data of GEM-listed companies during 2010 to 2015 for different high-tech industries. These models can ensure that the influencing factors of firm technological innovation performance are no longer restricted to a particular aspect but can provide a comprehensive comparative analysis of the effects of factors on firm technological innovation performance in different high-tech industries.

The empirical results show that R&D expenditures have a significant positive impact on firm technological innovation performance in most high-tech industries, but not in electronic and communication equipment manufacturing industry; R&D personnel investment and government subsidies have significant positive impacts on firm technological innovation performance in knowledge-oriented industries; technology diversity has a significant positive impact on firm technological innovation performance in technology-oriented industries; the proportion of exports shows an inverted U-shaped relationship with firm technological innovation performance in electronic and communication equipment manufacturing industry, while firm size shows an inverted U-shaped relationship with firm technological innovation performance in general equipment manufacturing industry; and the effect of semi-parametric model fit is superior to the general parameters model.

Drawing on the resource dependence perspective, this paper is the first to consider a comprehensive treatment of differential effects of internal resources (R&D personnel, R&D expenditure), external resources (government subsides) and firm characteristics (firm size, export ratio) on firm technological innovation performance in different high-tech industries in an emerging country, in particular in contrast to previous studies that have focused on a single industry or taken the type of industry as a control variable. In addition, most studies about the determinants of firm innovation performance are based on survey questionnaires, which may introduce large subjective errors. Setting the relationship between variables in advance may also introduce fit error when using a general-parameter model. Semi-parametric regression which is used in this paper is able to prevent this shortcoming effectively. When constructing a regression model, this can be exempted from the formal constraints, thus estimating data more accurately and ensuring superior fit.

We propose a nonparametric estimator of the Lorenz curve that satisfies its theoretical properties, including monotonicity and convexity. We adopt a transformation approach that transforms a constrained estimation problem into an unconstrained one, which is estimated nonparametrically. We utilize the splines to facilitate the numerical implementation of our estimator and to provide a parametric representation of the constructed Lorenz curve. We conduct Monte Carlo simulations to demonstrate the superior performance of the proposed estimator. We apply our method to estimate the Lorenz curve of the U.S. household income distribution and calculate the Gini index based on the estimated Lorenz curve.

We have developed in this paper a morphological disambiguation hybrid system for the Arabic language that identifies the stem, lemma and root of a given sentence words. Following an out-of-context analysis performed by the morphological analyser Alkhalil Morpho Sys, the system first identifies all the potential tags of each word of the sentence. Then, a disambiguation phase is carried out to choose for each word the right solution among those obtained during the first phase. This problem has been solved by equating the disambiguation issue with a surface optimization problem of spline functions. Tests have shown the interest of this approach and the superiority of its performances compared to those of the state of the art.

This paper aims to illustrate how a Bayesian approach to yield fitting can be implemented in a non-parametric framework with automatic smoothing inferred from the data. It also briefly illustrates the advantages of such an approach using real data.

The paper uses an infinite dimensional (functional space) approach to inverse problems. Numerical computations are carried out using a Markov Chain Monte-Carlo algorithm with several tweaks to ensure good performance. The model explicitly uses bid-ask spreads to allow for observation errors and provides automatic smoothing based on them.

A non-parametric framework allows to capture complex shapes of zero-coupon yield curves typical for emerging markets. Bayesian approach allows to assess the precision of estimates, which is crucial for some applications. Examples of estimation results are reported for three different bond markets: liquid (German), medium liquidity (Chinese) and illiquid (Russian).

The result shows that infinite-dimensional Bayesian approach to term structure estimation is feasible. Market practitioners could use this approach to gain more insight into interest rates term structure. For example, they could now be able to complement their non-parametric term structure estimates with Bayesian confidence intervals, which would allow them to assess statistical significance of their results.

The model does not require parameter tuning during estimation. It has its own parameters, but they are to be selected during model setup.

Applied research shows higher wages are associated with lower mobility at the establishment level. A usual interpretation is that high pay decreases labour turnover. The purpose of this paper is to test if such relationship holds for every type of worker in every type of firm.

The analysis is based on a linked employer-employee panel dataset covering the French private sector from 2002 to 2005. The authors compute establishment wage effects and use them as explanatory variables in labour mobility equations (for churning rate and quit rate). Using spline regression models enables to investigate for potential non-linearities.

The authors show that the relationship between churning rate and wage is non-linear and has the shape of an inverted J: the relation is negative and intense for establishments with low wage effect, weaker for average paying establishments and even becomes positive for very high-paying ones. This is true whatever the skill group of workers. It is also true for large establishments while the relationship is still negative but linear for small ones. The relationship between wages and quit rates has a strikingly similar pattern. This suggests that the link between churning and establishment wage effect is strongly related to quit decisions.

A possible interpretation of our results is that paying higher wages may be an effective stabilizing tool especially for employers in small establishments and when starting wages are relatively low.

The paper is the first to decompose the relationship between wage and mobility. It shows the relationship differs across establishment size and is not linear. The paper also shows quits play a role in this relationship.

The purpose of this paper is to describe and compare the mean response for selected financial variables in three dividend paying groups before and after the financial crisis of 2008. Dividend initiators are expected to be rewarded by investors over traditional dividend paying firms.

Quarterly CRSP data from 2000 to 2012 are used to define dividend paying groups. Highly unbalanced financial data on dividend paying firms are analyzed in two truncated sample periods defined before and after the financial crisis. Fitted models describing differences in dividend paying groups are based on the linear mixed model representation of penalized splines with random effects to account for repeated measures over time.

Results are presented on the important differences in selected financial variables before and after the financial crisis by dividend paying pattern group (traditional, initiators, residual/catering). Special emphasis is given to the analysis of market/book value ratio. Results demonstrate dividend initiators are rewarded over traditional dividend firms by investors. Firms with an intermittent paying pattern have no advantage. All dividend paying firms grow during the 2008 financial crisis. Traditional dividend payers have larger size than other dividend payers. The size effect explains results for several of the financial variables studied.

Future work can include an industry effect on the three dividend paying groups.

Investors appear to prefer certainty as to when they receive a dividend over uncertainty, especially in times of economic downturn and economic recovery.

Enhanced awareness that different payment patterns exist and are rewarded differently over time on both the corporate issuer and investor sides.

This study adds to body of knowledge of practical dividend payment patterns around a financial crisis. It also provides added support for dividend initiators.

This paper considers the problem of estimating a partially linear varying coefficient fixed effects panel data model. Using the series method, we establish the root N normality for the estimator of the parametric component; and we show that the unknown function can be consistently estimated at the standard nonparametric rate. Furthermore, we extend the model to allow endogeneity in the parametric component and establish the asymptotic properties of the semiparametric instrumental variable estimators.

The purpose of this paper is to explore the influence of a physician’s prosocial behavior on a patient's choices in the online health community (OHC) context. Moreover, the authors explore how such effects differ across different online word-of-mouth (WOM) and professional titles.

Guided by the motivation, opportunity and ability (MOA) framework, this paper develops hypotheses and an econometric model. Then this paper used spline regression to test hypotheses on 6,204 physicians at The Good Doctor (www.Haodf.com), which is one of the largest Chinese OHCs. The authors conducted the propensity score matching and difference-in-difference method (PSM-DID) to address the concern about the bias caused by possible endogeneity concerns.

The authors’ results show that a physician’s prosocial behavior improves a patient's choice only when the strength of a physician’s prosocial behavior is below the tipping point. In addition, the influence of a physician’s prosocial behavior is heterogeneous for physicians with different online WOM and professional titles. For physicians with higher online WOM, the effect of a physician's prosocial behaviors on a patient's choice is positive, while for physicians with lower online WOM, a physician’s prosocial behavior has no impact on a patient’s choice. For physicians with higher professional titles, the quantity of a physician’s prosocial behavior has a positive impact on a patient’s choice, while for physicians with lower professional titles the quality of a physician’s prosocial behavior has a positive impact on a patient’s choice.

This study contributes new knowledge and provides new perspectives to study a patient's choice by addressing the importance of physician's prosocial behavior. With the effort of explicitly explaining the complex mechanisms, this study encourages physicians' engagement in a physician’s prosocial behavior and gives some implications on how to perform the behaviors strategically.