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Articles 481 - 510 of 771
Full-Text Articles in Econometrics
Double Asymptotics For An Explosive Continuous Time Model, Xiaohu Wang, Jun Yu
Double Asymptotics For An Explosive Continuous Time Model, Xiaohu Wang, Jun Yu
Research Collection School Of Economics
This paper develops a double asymptotic limit theory for the persistent parameter (θ) in an explosive continuous time model with a large number of time span (N) and a small number of sampling interval (h). The limit theory allows for the joint limits where N → ∞ and h → 0 simultaneously, the sequential limits where N → ∞ is followed by h → 0, and the sequential limits where h → 0 is followed by N → ∞. All three asymptotic distributions are the same. The initial condition, either fixed or random, appears in the limiting distribution. The simultaneous …
Dating The Timeline Of Financial Bubbles During The Subprime Crisis, Peter C. B. Phillips, Jun Yu
Dating The Timeline Of Financial Bubbles During The Subprime Crisis, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
A new recursive regression methodology is introduced to analyze the bubble characteristics of various financial time series during the subprime crisis. The methods modify a technique proposed in Phillips, Wu, and Yu (2011) and provide a technology for identifying bubble behavior with consistent dating of their origination and collapse. The tests serve as an early warning diagnostic of bubble activity and a new procedure is introduced for testing bubble migration across markets. Three relevant financial series are investigated, including a financial asset price (a house price index), a commodity price (the crude oil price), and one bond price (the spread …
Specification Sensitivity In Right-Tailed Unit Root Testing For Explosive Behavior, Peter C. B. Phillips, Shu-Ping Shi, Jun Yu
Specification Sensitivity In Right-Tailed Unit Root Testing For Explosive Behavior, Peter C. B. Phillips, Shu-Ping Shi, Jun Yu
Research Collection School Of Economics
Right-tailed unit root tests have proved promising for detecting exuberance in economic and financial activities. Like left-tailed tests, the limit theory and test performance are sensitive to the null hypothesis and the model specification used in parameter estimation. This paper aims to provide some empirical guidelines for the practical implementation of right-tailed unit root tests, focusing on the sup ADF test of Phillips, Wu and Yu (2011), which implements a right-tailed ADF test repeatedly on a sequence of forward sample recursions. We analyze and compare the limit theory of the sup ADF test under deferent hypotheses and model specifications. The …
Specification Testing For Nonparametric Structural Models With Monotonicity In Unobservables, Stefan Hoderlein, Liangjun Su, Halbert White
Specification Testing For Nonparametric Structural Models With Monotonicity In Unobservables, Stefan Hoderlein, Liangjun Su, Halbert White
Research Collection School Of Economics
Monotonicity in a scalar unobservable is a now common assumption in economic theory and applications. Among other things, it allows one to recover the underlying structural function from certain conditional quantiles of observables. Nevertheless, monotonicity is a strong assumption, and its failure can have substantive adverse consequences for structural inference. So far, there are no generally applicable nonparametric specification tests designed to detect monotonicity failure. This paper provides such a test for cross-section data. We show how to exploit an exclusion restriction together with a conditional independence assumption, plausible in a variety of applications, to construct a test. Our statistic …
Linear Programming-Based Estimators In Simple Linear Regression, Daniel P. A. Preve, Marcelo C. Medeiros
Linear Programming-Based Estimators In Simple Linear Regression, Daniel P. A. Preve, Marcelo C. Medeiros
Research Collection School Of Economics
In this paper we introduce a linear programming estimator (LPE) for the slope parameter in a constrained linear regression model with a single regressor. The LPE is interesting because it can be superconsistent in the presence of an endogenous regressor and, hence, preferable to the ordinary least squares estimator (LSE). Two different cases are considered as we investigate the statistical properties of the LPE. In the first case, the regressor is assumed to be fixed in repeated samples. In the second, the regressor is stochastic and potentially endogenous. For both cases the strong consistency and exact finite-sample distribution of the …
Optimal Jackknife For Discrete Time And Continuous Time Unit Root Models, Ye Chen, Jun Yu
Optimal Jackknife For Discrete Time And Continuous Time Unit Root Models, Ye Chen, Jun Yu
Research Collection School Of Economics
Maximum likelihood estimation of the persistence parameter in the discrete time unit root model is known for su§ering from a downward bias. The bias is more pronounced in the continuous time unit root model. Recently Chambers and Kyriacou (2010) introduced a new jackknife method to remove the Örst order bias in the estimator of the persistence parameter in a discrete time unit root model. This paper proposes an improved jackknife estimator of the persistence parameter that works for both the discrete time unit root model and the continuous time unit root model. The proposed jackknife estimator is optimal in the …
Non-Parametric Regression Under Location Shifts, Peter C. B. Phillips, Liangjun Su
Non-Parametric Regression Under Location Shifts, Peter C. B. Phillips, Liangjun Su
Research Collection School Of Economics
Recent work by Wang and Phillips (2009b, 2011) has shown that ill-posed inverse problems do not arise in non-stationary non-parametric regression and there is no need for non-parametric instrumental variable estimation. Instead, simple Nadaraya–Watson non-parametric estimation of a cointegrating regression equation is consistent irrespective of the endogeneity in the regressor. The present paper shows that some closely related results apply in the case of structural non-parametric regression with independent data when there are continuous location shifts in the regressor. Some interesting cases are discovered where non-parametric regression is consistent, whereas parametric regression is inconsistent even when the true regression functional …
Tilted Nonparametric Estimation Of Volatility Functions With Empirical Applications, Ke-Li Xu, Peter C. B. Phillips
Tilted Nonparametric Estimation Of Volatility Functions With Empirical Applications, Ke-Li Xu, Peter C. B. Phillips
Research Collection School Of Economics
This article proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local-level nonparametric regression applied to squared residuals of the mean regression. The estimator is shown to be asymptotically equivalent to the local linear estimator in the case of unbounded support but, unlike that estimator, is restricted to be nonnegative in finite samples. It is fully adaptive to the unknown conditional mean function. Simulations are conducted to evaluate the finite-sample performance of the estimator. Two empirical applications are reported. One …
Bayesian Hypothesis Testing In Latent Variable Models, Yong Li, Jun Yu
Bayesian Hypothesis Testing In Latent Variable Models, Yong Li, Jun Yu
Research Collection School Of Economics
Hypothesis testing using Bayes factors (BFs) is known not to be well defined under the improper prior. In the context of latent variable models, an additional problem with BFs is that they are difficult to compute. In this paper, a new Bayesian method, based on decision theory and the EM algorithm, is introduced to test a point hypothesis in latent variable models. The new statistic is a by-product of the Bayesian MCMC output and, hence, easy to compute. It is shown that the new statistic is easy to interpret and appropriately defined under improper priors because the method employs a …
Simulated Maximum Likelihood Estimation For Latent Diffusion Models, Tore Selland Kleppe, Jun Yu, Hans J. Skaug
Simulated Maximum Likelihood Estimation For Latent Diffusion Models, Tore Selland Kleppe, Jun Yu, Hans J. Skaug
Research Collection School Of Economics
In this paper a method is developed and implemented to provide the simulated maximum likelihood estimation of latent diffusions based on discrete data. The method is applicable to diffusions that either have latent elements in the state vector or are only observed at discrete time with a noise. Latent diffusions are very important in practical applications in financial economics. The proposed approach synthesizes the closed form method of Ait-Sahalia (2008) and the efficient importance sampler of Richard and Zhang (2007). It does not require any infill observations to be introduced and hence is computationally tractable. The Monte Carlo study shows …
Testing For Multiple Bubbles, Peter C. B. Phillips, Shu-Ping Shi, Jun Yu
Testing For Multiple Bubbles, Peter C. B. Phillips, Shu-Ping Shi, Jun Yu
Research Collection School Of Economics
Identifying explosive bubbles that are characterized by periodically collapsing behavior over time has been a major concern in the literature and is of great importance for practitioners. The complexity of the nonlinear structure in multiple bubble phenomena diminishes the discriminatory power of existing tests, as evidenced in early simulations conducted by Evans (1991). Multiple collapsing bubble episodes within the same sample period make bubble diagnosis particularly difficult and complicate attempts at econometric dating. The present paper systematically investigates these issues and develops new procedures for practical implementation and surveillance strategies by central banks. We show how the testing procedure and …
Specification Sensitivities In Right-Tailed Unit Root Testing, Shu-Ping Shi, Peter C. B. Phillips, Jun Yu
Specification Sensitivities In Right-Tailed Unit Root Testing, Shu-Ping Shi, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
Right-tailed unit root tests have proved promising for detecting exuberance in economic and financial activities. Like left-tailed tests, the limit theory and test performance are sensitive to the null hypothesis and the model specification used in parameter estimation. This paper aims to provide some empirical guidelines for the practical implementation of right-tailed unit root tests, focusing on the sup ADF test of Phillips, Wu and Yu (2011), which implements a right-tailed ADF test repeatedly on a sequence of forward sample recursions. We analyze and compare the limit theory of the sup ADF test under different hypotheses and model specifications. The …
Instrumental Variable Quantile Estimation Of Spatial Autoregressive Models, Liangjun Su, Zhenlin Yang
Instrumental Variable Quantile Estimation Of Spatial Autoregressive Models, Liangjun Su, Zhenlin Yang
Research Collection School Of Economics
We propose a spatial quantile autoregression (SQAR) model, which allows cross-sectional dependence among the responses, unknown heteroscedasticity in the disturbances, and heterogeneous impacts of covariates on different points (quantiles) of a response distribution. The instrumental variable quantile regression (IVQR) method of Chernozhukov and Hansen (2006) is generalized to allow the data to be non-identically distributed and dependent, an IVQR estimator for the SQAR model is then defined, and its asymptotic properties are derived. Simulation results show that this estimator performs well in finite samples at various quantile points. In the special case of spatial median regression, it outperforms the conventional …
Bias In Estimating Multivariate And Univariate Diffusions, Xiaohu Wang, Peter C. B. Phillips, Jun Yu
Bias In Estimating Multivariate And Univariate Diffusions, Xiaohu Wang, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
Multivariate continuous time models are now widely used in economics and finance. Empirical applications typically rely on some process of discretization so that the system may be estimated with discrete data. This paper introduces a framework for discretizing linear multivariate continuous time systems that includes the commonly used Euler and trapezoidal approximations as special cases and leads to a general class of estimators for the mean reversion matrix. Asymptotic distributions and bias formulae are obtained for estimates of the mean reversion parameter. Explicit expressions are given for the discretization bias and its relationship to estimation bias in both multivariate and …
Asymptotic Theory For Zero Energy Functionals With Nonparametric Regression Applications, Qiying Wang, Peter C. B. Phillips
Asymptotic Theory For Zero Energy Functionals With Nonparametric Regression Applications, Qiying Wang, Peter C. B. Phillips
Research Collection School Of Economics
A local limit theorem is given for the sample mean of a zero energy function of a nonstationary time series involving twin numerical sequences that pass to infinity. The result is applicable in certain nonparametric kernel density estimation and regression problems where the relevant quantities are functions of both sample size and bandwidth. An interesting outcome of the theory in nonparametric regression is that the linear term is eliminated from the asymptotic bias. In consequence and in contrast to the stationary case, the Nadaraya-Watson estimator has the same limit distribution (to the second order including bias) as the local linear …
Infinite Density At The Median And The Typical Shape Of Stock Return Distributions, Chirok Han, Jin Seo Cho, Peter C. B. Phillips
Infinite Density At The Median And The Typical Shape Of Stock Return Distributions, Chirok Han, Jin Seo Cho, Peter C. B. Phillips
Research Collection School Of Economics
Statistics are developed to test for the presence of an asymptotic discontinuity (or infinite density or peakedness) in a probability density at the median. The approach makes use of work by Knight (1998) on L(1) estimation asymptotics in conjunction with nonparametric kernel density estimation methods. The size and power of the tests are assessed, and conditions under which the tests have good performance are explored in simulations. The new methods are applied to stock returns of leading companies across major U.S. industry groups. The results confirm the presence of infinite density at the median as a new significant empirical evidence …
Corrigendum To "A Gaussian Approach For Continuous Time Models Of The Short Term Interest Rate", Peter C. B. Phillips, Jun Yu
Corrigendum To "A Gaussian Approach For Continuous Time Models Of The Short Term Interest Rate", Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
An error is corrected in Yu and Phillips (2001) (Econometrics Journal, 4, 210-224) where a time transformation was used to induce Gaussian disturbances in the discrete time equivalent model. It is shown that the error process in this model is not a martingale and the Dambis, Dubins-Schwarz (DDS) theorem is not directly applicable. However, a detrended error process is a martingale, the DDS theorem is applicable, and the corresponding stopping time correctly induces Gaussianity. We show that the two stopping time sequences differ by O(a2), where a is the pre-specified normalized timing constant.
Explosive Behavior In The 1990s Nasdaq: When Did Exuberance Escalate Asset Values?, Peter C. B. Phillips, Yangru Wu, Jun Yu
Explosive Behavior In The 1990s Nasdaq: When Did Exuberance Escalate Asset Values?, Peter C. B. Phillips, Yangru Wu, Jun Yu
Research Collection School Of Economics
A recursive test procedure is suggested that provides a mechanism for testing explosive behavior, date stamping the origination and collapse of economic exuberance, and providing valid confidence intervals for explosive growth rates. The method involves the recursive implementation of a right-side unit root test and a sup test, both of which are easy to use in practical applications, and some new limit theory for mildly explosive processes. The test procedure is shown to have discriminatory power in detecting periodically collapsing bubbles, thereby overcoming a weakness in earlier applications of unit root tests for economic bubbles. An empirical application to the …
Nonparametric And Semiparametric Panel Econometric Models: Estimation And Testing, Liangjun Su, Aman Ullah
Nonparametric And Semiparametric Panel Econometric Models: Estimation And Testing, Liangjun Su, Aman Ullah
Research Collection School Of Economics
This paper gives a selective review on the recent developments of nonparametric and semiparametric panel data models. We focus on the conventional panel data models with one-way error component structure, partially linear panel data models, varying coefficient panel data models, nonparametric panel data models with multi-factor error structure, and nonseparable nonparametric panel data models. For each area, we discuss the basic models and ideas of estimation, and comment on the asymptotic properties of different estimators and specification tests. Much theoretical and empirical research is needed in this emerging area
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Research Collection School Of Economics
We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …
Testing Structural Change In Partially Linear Models, Liangjun Su, Halbert White
Testing Structural Change In Partially Linear Models, Liangjun Su, Halbert White
Research Collection School Of Economics
We consider two tests of structural change for partially linear time-series models. The first tests for structural change in the parametric component, based on the cumulative sums of gradients from a single semiparametric regression. The second tests for structural change in the parametric and nonparametric components simultaneously, based on the cumulative sums of weighted residuals from the same semiparametric regression. We derive the limiting distributions of both tests under the null hypothesis of no structural change and for sequences of local alternatives. We show that the tests are generally not asymptotically pivotal under the null but may be free of …
Need Singapore Fear Floating? A Dsge-Var Approach, Hwee Kwan Chow, Paul D. Mcnelis
Need Singapore Fear Floating? A Dsge-Var Approach, Hwee Kwan Chow, Paul D. Mcnelis
Research Collection School Of Economics
This paper uses a DSGE-VAR model to examine the managed exchange-rate system at work in Singapore and asks if the country has any reason to fear floating the exchange rate with a Taylor rule inflation-targeting mechanism that uses the short term interest rate instead of the exchange rate as the benchmark monetary policy instrument. Our simulation results show that the use of a more flexible exchange rate system will reduce volatility in inflation and investment but consumption volatility will increase. Overall, there are neither signi cant welfare gains or losses in the regime shift. Given the highly open and trade …
Smoothing Local-To-Moderate Unit Root Theory, Peter C. B. Phillips, Tassos Magdalinos, Liudas Giraitis
Smoothing Local-To-Moderate Unit Root Theory, Peter C. B. Phillips, Tassos Magdalinos, Liudas Giraitis
Research Collection School Of Economics
A limit theory is established for autoregressive time series that smooths the transition between local and moderate deviations from unity and provides a transitional form that links conventional unit root distributions and the standard normal. Edgeworth expansions of the limit theory are given. These expansions show that the limit theory that holds for values of the autoregressive coefficient that are closer to stationarity than local (i.e. deviations of the form rho = 1 + c/n, where n is the sample size and c < 0) holds up to the second order. Similar expansions around the limiting Cauchy density are provided for the mildly explosive case. (C) 2010 Elsevier B.V. All rights reserved.
Estimating The Garch Diffusion: Simulated Maximum Likelihood In Continuous Time, Tore Selland Kleppe, Jun Yu, Hans J. Skaug
Estimating The Garch Diffusion: Simulated Maximum Likelihood In Continuous Time, Tore Selland Kleppe, Jun Yu, Hans J. Skaug
Research Collection School Of Economics
A new algorithm is developed to provide a simulated maximum likelihood estimation of the GARCH diffusion model of Nelson (1990) based on return data only. The method combines two accurate approximation procedures, namely, the polynomial expansion of Ait-Sahalia (2008) to approximate the transition probability density of return and volatility, and the Efficient Importance Sampler (EIS) of Richard and Zhang (2007) to integrate out the volatility. The first and second order terms in the polynomial expansion are used to generate a base-line importance density for an EIS algorithm. The higher order terms are included when evaluating the importance weights. Monte Carlo …
Bayesian Hypothesis Testing In Latent Variable Models, Yong Li, Jun Yu
Bayesian Hypothesis Testing In Latent Variable Models, Yong Li, Jun Yu
Research Collection School Of Economics
Hypothesis testing using Bayes factors (BFs) is known to suffer from several problems in the context of latent variable models. The first problem is computational. Another problem is that BFs are not well defined under the improper prior. In this paper, a new Bayesian method, based on decision theory and the EM algorithm, is introduced to test a point hypothesis in latent variable models. The new statistic is a by-product of the Bayesian MCMC output and, hence, easy to compute. It is shown that the new statistic is appropriately defined under improper priors because the method employs a continuous loss …
A Conversation With Eric Ghysels, Peter C. B. Phillips, Jun Yu
A Conversation With Eric Ghysels, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
Eric Ghysels is the Bernstein Distinguished Professor of Economics and Professor of Finance at University of North Carolina at Chapel Hill. In 2008, Eric Ghysels and Robert Engle (2003 Nobel co-Laureate in Economic Science with Clive Granger) founded the Society for Financial Econometrics (SoFiE), establishing a global network of academics and practitioners dedicated to the fast-growing field of financial econometrics. In June 2010, Eric visited the Centre for Financial Econometrics (CoFiE) and the Sim Kee Boon Institute (SKBI) of Financial Economics at Singapore Management University. During his visit we conversed with him about SoFiE and the growing toolroom of financial …
Simulation-Based Estimation Methods For Financial Time Series Models, Jun Yu
Simulation-Based Estimation Methods For Financial Time Series Models, Jun Yu
Research Collection School Of Economics
This paper overviews some recent advances on simulatio n-based methods of estimating time series models and asset pricing models that are widely used in finance. The simulation based methods have proven to be particularly useful when the likelihood function and moments do not have tractable forms and hence the maximum likelihood method (MLE) and the generalized method of moments (GMM) are difficult to use. They can also be useful for improving the finite sample performance of the traditional methods when financial time series are highly persistent and when the quantity of interest is a highly nonlinear function of system parameters.The …
Standardized Lm Tests For Spatial Error Dependence In Linear Or Panel Regressions, Badi H. Baltagi, Zhenlin Yang
Standardized Lm Tests For Spatial Error Dependence In Linear Or Panel Regressions, Badi H. Baltagi, Zhenlin Yang
Research Collection School Of Economics
The robustness of the LM tests for spatial error dependence of Burridge (1980) for the linear regression model and Anselin (1988) for the panel regression model are examined. While both tests are asymptotic ally robust against distributional misspecification, their finite sample behavior can be sensitive to the spatial layout. To overcome this shortcoming, standardized LM tests are suggested. Monte Carlo results show that the new tests possess good finite sample properties. An important observation made throughout this study is that the LM tests for spatial dependence need to be both mean- and variance-adjusted for good finite sample performance to be …
A Study Of Price Evolution In Online Toy Market, Zhenlin Yang, Lydia L Gan, Fang-Fang Tang
A Study Of Price Evolution In Online Toy Market, Zhenlin Yang, Lydia L Gan, Fang-Fang Tang
Research Collection School Of Economics
We study and contrast pricing and price evolution of online only (Dotcom) and online branch of multi-channel retailers (OBMCRs) based on two panel data sets collected from online toy markets. Panel data regression analyses reveal several interesting empirical results: over time, OBMCRs and Dotcoms charge similar prices on average but Dotcoms significantly increase their shipping costs that eventually drive the overall average price of Dotcoms higher than that of OBMCRs. Price dispersions of both types of retailers are persistent. The price dispersion of OBMCRs is higher than that of Dotcoms at the beginning and does not change much over time, …