New Semiparametric Estimation Procedure for Functional Coefficient Longitudinal Data Models

2015 ◽  
Author(s):  
Jia Chen ◽  
Degui Li ◽  
Yingcun Xia
Keyword(s):  
Longitudinal Data ◽  
Semiparametric Estimation ◽  
Estimation Procedure ◽  
Data Models ◽  
Functional Coefficient

Fitting partially linear functional-coefficient panel-data models with Stata

2020 ◽  
Vol 20 (4) ◽  
pp. 976-998
Author(s):  
Kerui Du ◽  
Yonghui Zhang ◽  
Qiankun Zhou
Keyword(s):  
Monte Carlo ◽  
Panel Data ◽  
Fixed Effects ◽  
Linear Functional ◽  
Semiparametric Estimation ◽  
Data Models ◽  
Panel Data Models ◽  
Panel Models ◽  
Partially Linear ◽  
Functional Coefficient

In this article, we describe the implementation of fitting partially linear functional-coefficient panel models with fixed effects proposed by An, Hsiao, and Li [2016, Semiparametric estimation of partially linear varying coefficient panel data models in Essays in Honor of Aman Ullah ( Advances in Econometrics, Volume 36)] and Zhang and Zhou (Forthcoming, Econometric Reviews). Three new commands xtplfc, ivxtplfc, and xtdplfc are introduced and illustrated through Monte Carlo simulations to exemplify the effectiveness of these estimators.

scholarly journals Особливості застосування моделей лонгітюдних даних для сільськогосподарських підприємств

2013 ◽  
pp. 117-120
Author(s):  
Н. О. Окселенко
Keyword(s):  
Longitudinal Data ◽  
Significant Proportion ◽  
Data Models ◽  
Accounts Receivable ◽  
Agricultural Enterprises ◽  
Effective Current ◽  
Economic Interpretation ◽  
Assets Management

Робота розкриває питання вдосконалення процесу управління оборотними активами сільськогосподарських підприємств із використанням моделей лонгітюдних даних. Розроблено систему економетричних ANCOVA-моделей для сільськогосподарських підприємств. Подано економічне тлумачення всіх характеристик зв’язку та показано можливості використання моделей на практи-ці. Значну питому вагу оборотних активів сільськогоспо-дарських підприємств становлять запаси, дебіторська заборгованість, поточні біологічні активи. Доведено, що проблема ефективного управління оборотними актива-ми є водночас і проблемою управління прибутком. The work is devoted to the improvement of the current assets of management of the agricultural enterprises using the longitudinal data models. The system of econometric ANCOVA-models for agricultural enterprises is developed. The economic interpretation of all characteristics of the connection is given and the possibilities of the models use in practice are showed. Significant proportion of current assets of agricultural enterprises constitute reserves, accounts receivable, current biological assets. It was proved that the problem of the effective current assets management is at the same time a problem of profit management.

scholarly journals SEMIPARAMETRIC ESTIMATION OF RANDOM COEFFICIENTS IN STRUCTURAL ECONOMIC MODELS

2016 ◽  
Vol 33 (6) ◽  
pp. 1265-1305 ◽  
Author(s):  
Stefan Hoderlein ◽  
Lars Nesheim ◽  
Anna Simoni
Keyword(s):  
General Framework ◽  
Structural Model ◽  
Asymptotic Properties ◽  
Semiparametric Estimation ◽  
Estimation Method ◽  
Structural Models ◽  
Estimation Procedure ◽  
Random Coefficients ◽  
Random Parameters ◽  
Monte Carlo Experiments

This paper discusses nonparametric estimation of the distribution of random coefficients in a structural model that is nonlinear in the random coefficients. We establish that the problem of recovering the probability density function (pdf) of random parameters falls into the class of convexly-constrained inverse problems. The framework offers an estimation method that separates computational solution of the structural model from estimation. We first discuss nonparametric identification. Then, we propose two alternative estimation procedures to estimate the density and derive their asymptotic properties. Our general framework allows us to deal with unobservable nuisance variables, e.g., measurement error, but also covers the case when there are no such nuisance variables. Finally, Monte Carlo experiments for several structural models are provided which illustrate the performance of our estimation procedure.

Omitted variables in longitudinal data models

2001 ◽  
Vol 29 (4) ◽  
pp. 573-595 ◽  
Author(s):  
Edward W. Frees
Keyword(s):  
Longitudinal Data ◽  
Data Models ◽  
Omitted Variables

scholarly journals CoViD-19: an automatic, semiparametric estimation method for the population infected in Italy

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10819
Author(s):  
Livio Fenga
Keyword(s):  
Representative Sample ◽  
Semiparametric Estimation ◽  
Estimation Method ◽  
Estimation Procedure ◽  
Current Data ◽  
Regional Level ◽  
Reliable Estimation ◽  
Italian Government ◽  
The Future ◽  
Official Data

To date, official data on the number of people infected with the SARS-CoV-2—responsible for the Covid-19—have been released by the Italian Government just on the basis of a non-representative sample of population which tested positive for the swab. However a reliable estimation of the number of infected, including asymptomatic people, turns out to be crucial in the preparation of operational schemes and to estimate the future number of people, who will require, to different extents, medical attentions. In order to overcome the current data shortcoming, this article proposes a bootstrap-driven, estimation procedure for the number of people infected with the SARS-CoV-2. This method is designed to be robust, automatic and suitable to generate estimations at regional level. Obtained results show that, while official data at March the 12th report 12.839 cases in Italy, people infected with the SARS-CoV-2 could be as high as 105.789.

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