Many panel data have the latent subgroup effect on individuals, and it is important to correctly identify these groups since efficiency of resulting estimators can be improved significantly by pooling information individuals within each group. However, currently assumed parametric semiparametric relationship between response predictors may misspecified, which leads a wrong grouping result, nonp...

An inclusive development does not only rely on economic growth but also the creation of equitable access to outcomes. Government spending has an important role in promoting efficiency and as well equity. Meanwhile, financial inclusion is believed be able expand opportunities contribute growth. Previous studies have proven influence both with varying results. This study aims analyze impact gover...

Addressing the forecasting issues is one of core objectives developing and restructuring electric power industry in China. However, there are not enough efforts that have been made to develop an accurate electricity consumption procedure. In this paper, a panel semiparametric quantile regression neural network (PSQRNN) developed by combining artificial for data. By embedding penalized with leas...

Krol (1996) reports estimates of the saving-investment correlation, based on panel regressions, that are much lower than commonly found in the literature. This note argues that this low estimate is not related to the panel estimation technique, as Krol claims, but largely to the inclusion of Luxembourg in the sample. Panel estimation only reduces the correlation’s estimate by about 0.12. Octobe...

Traditional tools of welfare economics identify the envy-related welfare loss from conspicuous consumption only under very strong assumptions. Measured income and life satisfaction offers an alternative for estimating such consumption externalities. The approach is developed in the context of luxury car consumption (Ferraris and Porsches) in Switzerland. Results from household panel data and fi...

In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test betw...

The global energy system is highly vulnerable to climate variability and change. This results in a vast range of impacts on the demand sector production supply channels. article aims estimate variables such as heating cooling temperatures, income, population, price residential electricity G7 countries. Methodologically, this study uses second-generation panel unit root cointegration approaches ...

This paper studies estimation and inference in a quantile regression dynamic panel model with fixed effects. Panel data fixed effects estimators are typically biased in the presence of lagged dependent variables as regressors. To reduce the dynamic bias in the quantile regression fixed effects estimator I suggest the use of the instrumental variables quantile regression method of Chernozhukov a...