Semiparametric smooth coefficient models

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August undefined, 2024

WebThis paper considers a flexible semiparametric spatial autoregressive (mixed-regressive) model in which unknown coefficients are permitted to be nonparametric functions of some contextual variables to allow for potential nonlinearities and parameter heterogeneity in the spatial relationship. WebJun 11, 2024 · The semiparametric smooth coefficient specification in the SF model greatly facilitates our empirical investigation of the neutral and non-neutral effects of debt ratio. Many researchers work on the smooth coefficient structure in a regression setup.

A CONSISTENT NONPARAMETRIC TEST ON SEMIPARAMETRIC …

WebEnter the email address you signed up with and we'll email you a reset link. WebSep 22, 2024 · In this article, I describe the estimation of a particular type of semiparametric model known as the smooth varying-coefficient model (Hastie and Tibshirani, 1993, … bt broadband for business contact number

Semiparametric Model - an overview ScienceDirect Topics

WebAug 14, 2024 · In this paper we introduce the semiparametric smooth coefficient model proposed in Li et al. ( 2002) to the conditional mean specification of a recreation demand count data model. We are the first study that applies this particular modeling method with recreation demand data. WebWe investigate the semiparametric smooth coefficient stochastic frontier model for panel data in which the distribution of the composite error term is assumed to be of known form … WebAbstract. In this article, we consider the estimation of semiparametric panel data smooth coefficient models. We propose a class of local generalized method of moments (LGMM) estimators that are simple and easy to implement in practice. We show that the proposed LGMM estimators are consistent and asymptotically normal. exercise and plantar fasciitis

Semiparametric Smooth Coefficient Stochastic Frontier …

On the Estimation of Marginal Cost Operations Research

WebFeb 1, 2024 · We develop a two-step semiparametric procedure using a combination of local GMM and maximum likelihood approaches to estimate the unknown coefficient functions and other parameters of the model. The presence of a spatial component leads to several important methodological novelties. WebApr 25, 2024 · Semiparametric Estimation of Spatial Autoregressive Smooth-Coefficient Panel Stochastic Frontier Models April 2024 Semiparametric Spatial Autoregressive Stochastic Frontier Models... bt broadband flashing greenWebApr 13, 2024 · The GARCH model is one of the most influential models for characterizing and predicting fluctuations in economic and financial studies. However, most traditional GARCH models commonly use daily frequency data to predict the return, correlation, and risk indicator of financial assets, without taking data with other frequencies into account. … exercise and potassium levels

"WebOne of the most interesting forms of nonlinear regression models is the varying coefficient model (VCM). Unlike the linear regression model, VCMs were introduced by Hastie and … " - Semiparametric smooth coefficient models

Semiparametric smooth coefficient models

Smooth coefficient estimation of stochastic frontier models

WebFeb 24, 2015 · In this paper, we propose a simple nonparametric test for testing the null hypothesis of constant coefficients against nonparametric smooth coefficients in a … WebApr 25, 2024 · We propose a semiparametric varying-coefficient estimator that admits both qualitative and quantitative covariates along with a test for correct specification of …

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WebJul 2, 2024 · Abstract: We investigate the semiparametric smooth coefficient stochastic frontier model for panel data in which the distribution of the composite error term is assumed to be of known form but depends on som... Describe the main approaches discussed? Explain abstract in one line Describe practical implications of this paper Webof semiparametric varying coefficient models studied by Cai et al. (2009) and Xiao (2009), i.e. Yt = Xje(Zt) + u„ 1

WebAug 3, 2024 · A new semiparametric time series model is introduced – the semiparametric transition (SETR) model – that generalizes the threshold and smooth transition models by letting the transition function to be of an unknown form. WebJul 2, 2024 · The third chapter proposes a semiparametric additive stochastic frontier model for panel data, where inputs and environment variables can enter the frontier individually …

WebCai, Li, and Park ( Journal of Econometrics, 2009) and Xiao ( Journal of Econometrics, 2009) developed asymptotic theories for estimators of semiparametric varying coefficient … WebMay 1, 2024 · This article proposes a coefficients constancy test in semi-varying coefficient models that only needs to estimate the restricted coefficients under the null hypothesis. ... assuming that the varying coefficients are smooth enough. See for instance Kauermann and Tutz (1999), Cai et al. (2000), Fan and Zhang (2000), Fan et al. (2001), Li et al ...

WebMar 23, 2007 · Our models extend the non-linear factor analysis model of Yalcin and Amemiya (2001) to incorporate semiparametric regression through penalized spline smoothing for the structural component of the model. The general form of model (1) can be extended to more than one latent variable, if subject-matter theory suggests that such a …

WebDec 15, 2024 · We therefore re-investigate the impact of natural disasters on economic growth, applying a semiparametric smooth coefficient panel data model that takes into account fixed effects. Our... bt broadband for business reviewsWebregression model: a semiparametric smooth coefficient model. A semiparametric smooth coefficient model nests a partially linear model as a special case and it is given by Yi = … exercise and play golf setWebAug 1, 2013 · More recently, Sun and Kumbhakar (2013) and Yao, Zhang, and Kumbhakar (2024) proposed the semiparametric smooth coefficient (SPSC) stochastic production frontier model, in which the input... exercise and prostate cancer preventionWebSep 1, 2024 · It is known that semiparametric time series regression is often used without checking its suitability and compactness. In theory, this may result in dealing with an unnecessarily complicated... bt broadband for my postcodeWebDemographic Models. Y. Xie, in International Encyclopedia of the Social & Behavioral Sciences, 2001 4 Semiparametric Models. In response to these problems with parametric … exercise and protein intakeWebJan 1, 2024 · Efficient and adaptive estimation for semiparametric models, volume 4. Johns Hopkins University Press Baltimore, 1993. ... Smooth, identifiable supermodels of discrete DAG models with latent variables. ... and Lue Ping Zhao. Estimation of regression coefficients when some regressors are not always observed. Journal of the American … exercise and prostate cancer progressionWebJan 1, 2012 · Abstract. In this article, we propose a semiparametric smooth coefficient model as a useful yet flexible specification for studying a general regression relationship with varying coefficients. The article proposes a local least squares method with a kernel … exercise and restless leg