Zongwu Cai, Jingping Gu and Qi Li
There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments…
Abstract
There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.
Han-Ying Liang, Yu Shen and Qiying Wang
Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two…
Abstract
Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two decades have witnessed a surge of interest in modeling nonlinear nonstationarity in macroeconomic and financial time series, including parametric, nonparametric and semiparametric specifications of such models. These developments have provided a framework of econometric estimation and inference for a wide class of nonlinear, nonstationary relationships. In honor of Joon Y. Park, this chapter contributes to this area by exploring nonparametric estimation of functional-coefficient cointegrating regression models where the structural equation errors are serially dependent and the regressor is endogenous. The self-normalized local kernel and local linear estimators are shown to be asymptotic normal and to be pivotal upon an estimation of co-variances. Our new results improve those of Cai et al. (2009) and open up inference by conventional nonparametric method to a wide class of potentially nonlinear cointegrated relations.
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This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric…
Abstract
This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.
An Yonghong, Hsiao Cheng and Li Dong
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…
Abstract
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.
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Yiguo Sun, Raymond J. Carroll and Dingding Li
We consider the problem of estimating a varying coefficient panel data model with fixed-effects (FE) using a local linear regression approach. Unlike first-differenced estimator…
Abstract
We consider the problem of estimating a varying coefficient panel data model with fixed-effects (FE) using a local linear regression approach. Unlike first-differenced estimator, our proposed estimator removes FE using kernel-based weights. This results a one-step estimator without using the backfitting technique. The computed estimator is shown to be asymptotically normally distributed. A modified least-squared cross-validatory method is used to select the optimal bandwidth automatically. Moreover, we propose a test statistic for testing the null hypothesis of a random-effects varying coefficient panel data model against an FE one. Monte Carlo simulations show that our proposed estimator and test statistic have satisfactory finite sample performance.
Marine Carrasco and Idriss Tsafack
This chapter proposes a nonparametric estimator of the risk neutral density (RND) based on cross-sectional European option prices. The authors recast the arbitrage-free equation…
Abstract
This chapter proposes a nonparametric estimator of the risk neutral density (RND) based on cross-sectional European option prices. The authors recast the arbitrage-free equation for option pricing as a functional linear regression model where the regressor is a curve and the independent variable is a scalar corresponding to the option price. Then, the authors show that the RND can be viewed as the solution of an ill-posed integral equation. To estimate the RND, the authors use an iterative method called Landweber-Fridman (LF). Then, the authors establish the consistency and asymptotic normality of the estimated RND. These results can be used to construct a confidence interval around the curve. Finally, some Monte Carlo simulations and application to the S&P 500 options show that this method performs well compared to alternative methods.
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This chapter develops an asymptotic theory for a general transformation model with a time trend, stationary regressors, and unit root nonstationary regressors. This model extends…
Abstract
This chapter develops an asymptotic theory for a general transformation model with a time trend, stationary regressors, and unit root nonstationary regressors. This model extends that of Han (1987) to incorporate time trend and nonstationary regressors. When the transformation is specified as an identity function, the model reduces to the conventional cointegrating regression, possibly with a time trend and other stationary regressors, which has been studied in Phillips and Durlauf (1986) and Park and Phillips (1988, 1989). The limiting distributions of the extremum estimator of the transformation parameter and the plug-in estimators of other model parameters are found to critically depend upon the transformation function and the order of the time trend. Simulations demonstrate that the estimators perform well in finite samples.
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Shengbin Ma, Zhongfu Li, Long Li and Mengqi Yuan
The coordinated development of the urbanization and construction industry is crucial for the sustainable development of cities. However, the coupling relationship and coordination…
Abstract
Purpose
The coordinated development of the urbanization and construction industry is crucial for the sustainable development of cities. However, the coupling relationship and coordination mechanism between them remain unclear. To bridge this gap, this study attempts to explore the level of coupling coordination between new urbanization and construction industry development and investigate the critical driving factors influencing their coupling coordination degree.
Design/methodology/approach
By referring to the existing literature, two index systems were established to evaluate the development level of the new urbanization and construction industry. The spatiotemporal characteristics of the coupled coordinated development of the new urbanization and construction industry in China from 2014 to 2020 were investigated using the coupling coordination model. The Markov chain and geographic detector were adopted to understand the transition probability and driving factors of the coupling coordination degree.
Findings
The results indicate that the coupling degree of China's new urbanization and construction industry is high, and the two systems exhibit obvious interaction phenomena. However, the construction industry in most provinces lags behind the new urbanization. A positive interactive relationship and coordination mechanism has not been established between the two systems. Furthermore, the coupling contribution degree of the driving factors from high to low is as follows: market size > labor resource concentration > government investment ability > economic development level > industrial structure > production efficiency > technology level. Accordingly, a driving mechanism including market, policy, economic, and production technology drivers was developed.
Originality/value
This study contributes to the existing body of knowledge by providing a set of scientific analysis methods to address the deficiency of coordination mechanism research on new urbanization and the construction industry. The results also provide a theoretical basis for decision makers to develop differentiated sustainable development policies.
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Arash Tavakoli, M. Pourseifi and Sara Rezaei
The purpose of this paper is to provide a theoretical analysis of the fracture behavior of multiple axisymmetric interface cracks between a homogeneous isotropic layer and its…
Abstract
Purpose
The purpose of this paper is to provide a theoretical analysis of the fracture behavior of multiple axisymmetric interface cracks between a homogeneous isotropic layer and its functionally graded material (FGM) coating under torsional loading.
Design/methodology/approach
In this paper, the authors employ the distributed dislocation technique to the stress analysis, an FGM coating-substrate system under torsional loading with multiple axisymmetric cracks consist of annular and penny-shaped cracks. First, with the aid of the Hankel transform, the stress fields in the homogeneous layer and its FGM coating are obtained. The problem is then reduced to a set of singular integral equations with a Cauchy-type singularity. Unknown dislocation density is achieved by numerical solution of these integral equations which are employed to calculate the SIFs.
Findings
From the numerical results, the following key points were observed: first, for two types of the axisymmetric interface cracks, the SIFs decrease with growing in the values of the non-homogeneity. Second, the SIFs increase with increases in interface crack length. Third, the magnitude of the SIFs decreases with increases in the FGM coating thickness. Fourth, the interaction between cracks is an important factor affecting the SIFs of crack tips.
Originality/value
New analytical dislocation solution in an FGM coating-substrate system is developed.
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This study aims to perform dynamic response analysis of damaged rigid-frame bridges under multiple moving loads using analytical based transfer matrix method (TMM). The effects of…
Abstract
Purpose
This study aims to perform dynamic response analysis of damaged rigid-frame bridges under multiple moving loads using analytical based transfer matrix method (TMM). The effects of crack depth, moving load velocity and damping on the dynamic response of the model are discussed. The dynamic amplifications are investigated for various damage scenarios in addition to displacement time-histories.
Design/methodology/approach
Timoshenko beam theory (TBT) and Rayleigh-Love bar theory (RLBT) are used for bending and axial vibrations, respectively. The cracks are modeled using rotational and extensional springs. The structure is simplified into an equivalent single degree of freedom (SDOF) system using exact mode shapes to perform forced vibration analysis according to moving load convoy.
Findings
The results are compared to experimental data from literature for different damaged beam under moving load scenarios where a good agreement is observed. The proposed approach is also verified using the results from previous studies for free vibration analysis of cracked frames as well as dynamic response of cracked beams subjected to moving load. The importance of using TBT and RLBT instead of Euler–Bernoulli beam theory (EBT) and classical bar theory (CBT) is revealed. The results show that peak dynamic response at mid-span of the beam is more sensitive to crack length when compared to moving load velocity and damping properties.
Originality/value
The combination of TMM and modal superposition is presented for dynamic response analysis of damaged rigid-frame bridges subjected to moving convoy loading. The effectiveness of transfer matrix formulations for the free vibration analysis of this model shows that proposed approach may be extended to free and forced vibration analysis of more complicated structures such as rigid-frame bridges supported by piles and having multiple cracks.