Varying coefficient panel data model in the presence of endogenous selectivity and fixed effects

Malikov, Emir; Kumbhakar, Subal C.; Sun, Yiguo

doi:10.1016/j.jeconom.2015.06.007

Cited by 16 publications

(6 citation statements)

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“…A panel data set is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models (PDM) have become increasingly popular due to their heightened capacity for capturing the complexity of behavior as compared to cross–sectional or time–series data models (Hsiao, 2005; Malikov et al, 2016).…”

Section: Vcms For Zoned Uplift Pressure Piezometersmentioning

confidence: 99%

Zoned safety monitoring model for uplift pressures of concrete dams

2019

Transactions of the Institute of Measurement and Control

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Uplift pressure beneath concrete dams is related to several intrinsic factors such as geological structure, qualities of grouting and drainage engineering, and so forth. Thus, the fluctuation law and the amplitude of the uplift pressure vary along the dam axis. Based on observation data, the data mining method can be used to divide the piezometers beneath concrete dams into several zones, with similar fluctuation laws in measurement, to better identify the spatial distribution mechanism of the foundation uplift pressure. Then, zoned regression models can be established to mine the essential causes of the abnormal zone. In this paper, data mining algorithms such as time series piecewise representation, similarity measure and cluster analysis are combined to propose the zoning method for piezometers. On this basis, the variable coefficient panel data model is employed to establish regression models of various zones of piezometers. The Xixi Reservoir Dam is taken as a case study. According to the supplementary geological survey result, the credibility of the proposed method is verified. Further discussion shows that the causes of the sudden increases of the abnormal zone under the unfavorable condition include the development of local rock fissures, the aging of the grouting curtain. The observation data after the curtain reinforcement shows that uplift pressures in the abnormal zone are getting normal. The proposed method can also be easily applied to the zoned safety monitoring of arch dam deformation, reservoir slope stability, lateral bypass seepage, and so forth.

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Section: Vcms For Zoned Uplift Pressure Piezometersmentioning

confidence: 99%

Zoned safety monitoring model for uplift pressures of concrete dams

2019

Transactions of the Institute of Measurement and Control

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“…We exclude corporate credit unions (whose customers are the retail credit unions) from the sample in order to minimize noise in the data due to apparent non-homogeneity between these two types of financial depositories. Sinceỹ and w 1 are interest rates, we follow Wilson (2011) andMalikov et al (2016) and also eliminate those observations for which values of these variables lie outside the unit interval. We intentionally limit our analysis to a pre-crisis period in an attempt to minimize the influence of potential structural changes in the industry during the crisis and in its aftermath on the estimation results.…”

Section: Datamentioning

confidence: 99%

“…The latter has recently become a subject of particular scholarly interest (e.g., Emmons & Schmid, 1999;Malikov et al, 2015bMalikov et al, , 2016Wheelock & Wilson, 2011;Wilcox, 2005Wilcox, , 2006. We next proceed to measuring the degree of scale economies (if any) exhibited by credit unions.…”

Section: Figure 2 Kernel Densities Of Economies Of Diversification Acmentioning

confidence: 99%

Economies of diversification in the US credit union sector

Malikov

Zhao

Kumbhakar

2017

J of Applied Econometrics

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Summary Significant scale economies have been recently cited to rationalize a dramatic growth in the US retail credit union sector over the past few decades. In this paper, we explore another plausible supply‐side explanation for the growth of the industry, namely economies of diversification. We focus on the fact that credit unions differ among themselves in the range of financial services they offer to their members. Since larger credit unions tend to offer a more diversified financial service menu than credit unions of a smaller size, the incentive to grow in size may be fueled not only by present scale economies but also by economies of diversification. This paper provides the first robust estimates of such economies of diversification for the credit union sector. We estimate a flexible semiparametric smooth coefficient quantile panel data model with correlated effects that is capable of accommodating a four‐way heterogeneity among credit unions. Our results indicate the presence of non‐negligible economies of diversification in the industry. We find that as many as 27–91% (depending on the type and the cost quantile) of diversified credit unions enjoy substantial economies of diversification; the cost of most remaining credit unions is invariant to the scope of services. We also find overwhelming evidence of increasing returns to scale in the industry.

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“…For example, Sun et al (2009) (2015) considered the variable selection for the model using the basis function approximations and the group nonconcave penalized functions. Malikov et al (2016) considered the problem of varying coefficient panel data model in the presence of endogenous selectivity and fixed effects. In addition, if λ i ≡ 0 or F t ≡ 0, model (2) reduces to the varying coefficient model with panel data.…”

Section: Introductionmentioning

confidence: 99%

Varying Coefficient Panel Data Model with Interactive Fixed Effects

Feng

Peng³

et al. 2021

STAT SINICA

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In this paper, we propose a varying coefficient panel data model with unobservable multiple interactive fixed effects that are correlated with the regressors. We approximate each coefficient function by B-spline, and propose a robust nonlinear iteration scheme based on the least squares method to estimate the coefficient functions of interest. We also establish the asymptotic theory of the resulting estimators under certain regularity assumptions, including the consistency, the convergence rate and the asymptotic distribution. Furthermore, we develop a least squares dummy variable method to study an important special case of the proposed model: the varying coefficient panel data model with additive fixed effects. To construct the pointwise confidence intervals for the coefficient functions, a residual-based block bootstrap method is proposed to reduce the computational burden as well as to avoid the accumulative errors. Simulation studies and a real data analysis are also carried out to assess the performance of our proposed methods.

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Varying coefficient panel data model in the presence of endogenous selectivity and fixed effects

Cited by 16 publications

References 50 publications

Zoned safety monitoring model for uplift pressures of concrete dams

Zoned safety monitoring model for uplift pressures of concrete dams

Economies of diversification in the US credit union sector

Varying Coefficient Panel Data Model with Interactive Fixed Effects

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