Econometrics Commons^™

Bootstrap Lm Tests For Higher-Order Spatial Effects In Spatial Linear Regression Models, Zhenlin Yang

Research Collection School Of Economics

This paper first extends the methodology of Yang (J Econom 185:33-59, 2015) to allow for non-normality and/or unknown heteroskedasticity in obtaining asymptotically refined critical values for the LM-type tests through bootstrap. Bootstrap refinements in critical values require the LM test statistics to be asymptotically pivotal under the null hypothesis, and for this we provide a set of general methods for constructing LM and robust LM tests. We then give detailed treatments for two general higher-order spatial linear regression models: namely the model and the model, by providing a complete set of non-normality robust LM and bootstrap LM tests for higher-order …

Financial Bubble Implosion And Reverse Regression, Peter C. B. Phillips, Shu-Ping Shi

Research Collection School Of Economics

Expansion and collapse are two key features of a financial asset bubble. Bubble expansionmay be modeled using a mildly explosive process. Bubble implosion may take several differentforms depending on the nature of the collapse and therefore requires some flexibility in modeling.This paper first strengthens the theoretical foundation of the real time bubble monitoringstrategy proposed in Phillips, Shi and Yu (2015a,b, PSY) by developing analytics and studyingthe performance characteristics of the testing algorithm under alternative forms of bubbleimplosion which capture various return paths to market normalcy. Second, we propose a newreverse sample use of the PSY procedure for detecting crises and …

Boundary Limit Theory For Functional Local To Unity Regression, Anna Bykhovskaya, Peter C. B. Phillips

Research Collection School Of Economics

This article studies functional local unit root models (FLURs) in which the autoregressive coefficient may vary with time in the vicinity of unity. We extend conventional local to unity (LUR) models by allowing the localizing coefficient to be a function which characterizes departures from unity that may occur within the sample in both stationary and explosive directions. Such models enhance the flexibility of the LUR framework by including break point, trending, and multidirectional departures from unit autoregressive coefficients. We study the behavior of this model as the localizing function diverges, thereby determining the impact on the time series and on …

Asymptotics And Bootstrap For Random-Effects Panel Data Transformation Models, Liangjun Su, Zhenlin Yang

Research Collection School Of Economics

This article investigates the asymptotic properties of quasi-maximum likelihood (QML) estimators for random-effects panel data transformation models where both the response and (some of) the covariates are subject to transformations for inducing normality, flexible functional form, homoskedasticity, and simple model structure. We develop a QML-type procedure for model estimation and inference. We prove the consistency and asymptotic normality of the QML estimators, and propose a simple bootstrap procedure that leads to a robust estimate of the variance-covariance (VC) matrix. Monte Carlo results reveal that the QML estimators perform well in finite samples, and that the gains by using the robust …

Diagnostic Tests For Homoskedasticity In Spatial Cross-Sectional Or Panel Models, Badi H. Baltagi, Alain Pirotte, Zhenlin Yang

Research Collection School Of Economics

We propose tests for homoskedasticity in spatial econometric models, based on joint or concentrated score functions and an Outer-Product-of-Martingale-Difference (OPMD) estimate of the variance of the joint or concentrated score functions. Versions of these tests robust against non-normality are also given. Asymptotic properties of the proposed tests are formally examined using a cross-section model and a panel model with fixed effects. Monte Carlo results show that the proposed tests based on the concentrated score function have good finite sample properties. Finally, the generality of the proposed approach in constructing tests for homoskedasticity is further demonstrated using a spatial dynamic panel …

New Distribution Theory For The Estimation Of Structural Break Point In Mean, Liang Jiang, Xiaohu Wang, Jun Yu

Research Collection School Of Economics

Based on the Girsanov theorem, this paper obtains the exact distribution of the maximum likelihood estimator of structural break point in a continuous time model. The exact distribution is asymmetric and tri-modal, indicating that the estimator is biased. These two properties are also found in the finite sample distribution of the least squares (LS) estimator of structural break point in the discrete time model, suggesting the classical long-span asymptotic theory is inadequate. The paper then builds a continuous time approximation to the discrete time model and develops an in-fill asymptotic theory for the LS estimator. The in-fill asymptotic distribution is …

The Heterogeneous Effects Of The Minimum Wage On Employment Across States, Wuyi Wang, Peter C. B. Phillips, Liangjun Su

Research Collection School Of Economics

This paper studies the relationship between the minimum wage and the employment rate in the US using the framework of a panel structure model. The approach allows the minimum wage, along with some other controls, to have heterogeneous effects on employment across states which are classified into a group structure. The effects on employment are the same within each group but differ across different groups. The number of groups and the group membership of each state are both unknown a priori. The approach employs the C-Lasso technique, a recently developed classification method that consistently estimates group structure and leads to …

Dispersion And Uncertainty In Density Forecasts: Evidence From Surveys Of Professional Forecasters, You Li

Dissertations and Theses Collection (Open Access)

This dissertation studies patterns of dispersion in density forecasts as reported in surveys of professional forecasters. We pay special attention to the role of uncertainty in explaining dispersion in professional forecasters’ density forecasts of real output growth and inflation. We also consider the relationship between survey design and forecaster behavior. The last chapter describes future research exploring the characteristics of forecaster expectations using probability integral transforms.

As a starting point, chapter one gives a summary of the literature that tries to answer, using data from survey of forecasters, the following three key questions: Why do forecasters disagree? What do density …

Three Essays On Panel Structure Models, Wuyi Wang

Dissertations and Theses Collection (Open Access)

In panel structure models, individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups, both the number of groups and each individual’s group membership are unknown. This dissertation proposes some methods to identify the panel structure models under different specifications, namely, developing a Lasso-type Panel-CARDS method in the linear panel, constructing two sequential binary segmentation algorithms in the nonlinear panel, and using K-means algorithm in the spatial panel.

Chapter 2 studies the estimation of a linear panel data model with latent structures. To identify the unknown group structure of …

A Dynamic Network Perspective On The Latent Group Structure Of Cryptocurrencies, Li Guo, Yubo Tao, Wolfgang Karl Hardle

Research Collection School Of Economics

In this paper, we study the latent group structure in cryptocurrencies market by forming a dynamic return inferred network with coin attributions. We develop a dynamic covariate-assisted spectral clustering method to detect the communities in dynamic network framework and prove its uniform consistency along the horizons. Applying our new method, we show the return inferred network structure and coin attributions, including algorithms and proof types, jointly determine the market segmentation. Based on the network model, we propose a novel "hard-to-value" measure using the centrality scores. Further analysis reveals that the group with a lower centrality score exhibits stronger short-term return …

Asymptotic Inference About Predictive Accuracy Using High Frequency Data, Jia Li, Andrew J. Patton

Research Collection School Of Economics

This paper provides a general framework that enables many existing inference methods for predictive accuracy to be used in applications that involve forecasts of latent target variables. Such applications include the forecasting of volatility, correlation, beta, quadratic variation, jump variation, and other functionals of an underlying continuous-time process. We provide primitive conditions under which a “negligibility” result holds, and thus the asymptotic size of standard predictive accuracy tests, implemented using a high-frequency proxy for the latent variable, is controlled. An extensive simulation study verifies that the asymptotic results apply in a range of empirically relevant applications, and an empirical application …

Determination Of Different Types Of Fixed Effects In Three-Dimensional Panels, Xun Lu, Ke Miao, Liangjun Su

Research Collection School Of Economics

In this paper we propose a jackknife method to determine the type of fixed effects in three-dimensional panel data models. We show that with probability approaching 1, the method can select the correct type of fixed effects in the presence of only weak serial or cross-sectional dependence among the error terms. In the presence of strong serial correlation, we propose a modified jackknife method and justify its selection consistency. Monte Carlo simulations demonstrate the excellent finite sample performance of our method. Applications to two datasets in macroeconomics and international trade reveal the usefulness of our method.

Extremal Quantile Regressions For Selection Models And The Black-White Wage Gap, Xavier D'Haultfoeuille, Arnaud Maurel, Yichong Zhang

Research Collection School Of Economics

We consider the estimation of a semiparametric sample selection model without instrument or large support regressor. Identification relies on the independence between the covariates and selection, for arbitrarily large values of the outcome. We propose a simple estimator based on extremal quantile regression and establish its asymptotic normality by extending previous results on extremal quantile regressions to allow for selection. Finally, we apply our method to estimate the black-white wage gap among males from the NLSY79 and NLSY97. We find that premarket factors such as AFQT and family background play a key role in explaining the black-white wage gap.

Integrated Deviance Information Criterion For Latent Variable Models, Yong Li, Jun Yu, Tao Zeng

Research Collection School Of Economics

Deviance information criterion (DIC) has been widely used for Bayesian model comparison, especially after Markov chain Monte Carlo (MCMC) is used to estimate candidate models. This paper studies the problem of using DIC to compare latent variable models after the models are estimated by MCMC together with the data augmentation technique. Our contributions are twofold. First, we show that when MCMC is used with data augmentation, it undermines theoretical underpinnings of DIC. As a result, by treating latent variables as parameters, the widely used way of constructing DIC based on the conditional likelihood, although facilitating computation, should not be used. …

Return And Volatility Spillovers Between The Renminbi And Asian Currencies, Hwee Kwan Chow-Tan

Research Collection School Of Economics

This paper examines the extent of interdependence between the Chinese Renminbi and Asian currenciesafter the global financial crisis. We combine the distinct influence of offshore Renminbi with the impact ofthe onshore rate on eight Asian currencies (including the Australian dollar). Diebold-Yilmaz spilloverindexes reveal Asian foreign exchange markets are subject to considerable cross-border transmissions. Interms of the US dollar bilateral exchange rates, cross-border transfers of daily return are strongercompared to daily volatility reflecting currency management by regional authorities to curb excessiveexchange rate volatility. Return spillovers from the Renminbi markets to individual Asian foreignexchange markets are generally on par with that from …

Sequentially Testing Polynomial Model Hypotheses Using Power Transforms Of Regressors, Jin Seo Cho, Peter C. B. Phillips

Research Collection School Of Economics

We provide a methodology for testing a polynomial model hypothesis by generalizing the approach and results of Baek, Cho, and Phillips (Journal of Econometrics, 2015, 187, 376–384; BCP), which test for neglected nonlinearity using power transforms of regressors against arbitrary nonlinearity. We use the BCP quasi-likelihood ratio test and deal with the new multifold identification problem that arises under the null of the polynomial model. The approach leads to convenient asymptotic theory for inference, has omnibus power against general nonlinear alternatives, and allows estimation of an unknown polynomial degree in a model by way of sequential testing, a technique that …

Extremal Quantile Treatment Effects, Yichong Zhang

Research Collection School Of Economics

This paper establishes an asymptotic theory and inference method for quantile treatment effect estimators when the quantile index is close to or equal to zero. Such quantile treatment effects are of interest in many applications, such as the effect of maternal smoking on an infant’s adverse birth outcomes. When the quantile index is close to zero, the sparsity of data jeopardizes conventional asymptotic theory and bootstrap inference. When the quantile index is zero, there are no existing inference methods directly applicable in the treatment effect context. This paper addresses both of these issues by proposing new inference methods that are …

Pythagorean Generalization Of Testing The Equality Of Two Symmetric Positive Definite Matrices, Jin Seo Cho, Peter C. B. Phillips

Research Collection School Of Economics

We provide a new test for equality of two symmetric positive-definite matrices that leads to a convenient mechanism for testing specification using the information matrix equality or the sandwich asymptotic covariance matrix of the GMM estimator. The test relies on a new characterization of equality between two k dimensional symmetric positive-definite matrices A and B: the traces of AB−1 and BA−1 are equal to k if and only if A=B. Using this simple criterion, we introduce a class of omnibus test statistics for equality and examine their null and local alternative approximations under some mild regularity conditions. A preferred test …

Volatility Spillovers And Linkages In Asian Stock Markets, Hwee Kwan Chow

Research Collection School Of Economics

Diebold–Yilmaz spillover indexes are computed for weekly return volatilities based on daily benchmark stock indexes of the US, the UK, and 10 Asian countries. We found (i) the strengthening of overall volatility spillovers is not a temporary surge but persisted after the crisis; (ii) the susceptibility of individual Asian stock markets to inward volatility transfers is linked to its degree of openness; and (iii) the Asian bourses are becoming more important emitters of financial shocks since the crisis. Rolling regressions on volatility linkages reveal the relative dominance of the US over the Japanese and Chinese bourses, and the level of …

Business Time Sampling Scheme With Applications To Testing Semi-Martingale Hypothesis And Estimating Integrated Volatility, Yingjie Dong, Yiu Kuen Tse

Research Collection School Of Economics

We propose a new method to implement the Business Time Sampling (BTS) scheme for high-frequency financial data. We compute a time-transformation (TT) function using the intraday integrated volatility estimated by a jump-robust method. The BTS transactions are obtained using the inverse of the TT function. Using our sampled BTS transactions, we test the semi-martingale hypothesis of the stock log-price process and estimate the daily realized volatility. Our method improves the normality approximation of the standardized business-time return distribution. Our Monte Carlo results show that the integrated volatility estimates using our proposed sampling strategy provide smaller root mean-squared error.

Bayesian Analysis Of Bubbles In Asset Prices, Andras Fulop, Jun Yu

Research Collection School Of Economics

We develop a new asset price model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a stochastic long run mean. This latter is allowed to account for possible smooth structural change. The second regime reflects the bubble period with explosive behavior. Stochastic switches between two regimes and non-constant probabilities of exit from the bubble regime are both allowed. A Bayesian learning approach is employed to jointly …

Identifying Latent Group Structures In Nonlinear Panels, Wuyi Wang, Liangjun Su

Research Collection School Of Economics

We propose a procedure to identify latent group structures in nonlinear panel data models where some regression coefficients are heterogeneous across groups but homogeneous within a group and the group number and membership are unknown. To identify the group structures, we consider the order statistics for the preliminary unconstrained consistent estimators of the regression coefficients and translate the problem of classification into the problem of break detection. Then we extend the sequential binary segmentation algorithm of Bai (1997) for break detection from the time series setup to the panel data framework. We demonstrate that our method is able to identify …

Inference In Continuous Systems With Mildly Explosive Regressors, Ye Chen, Peter C. B. Phillips, Jun Yu

Research Collection School Of Economics

New limit theory is developed for co-moving systems with explosive processes, connecting continuous and discrete time formulations. The theory uses double asymptotics with infill (as the sampling interval tends to zero) and large time span asymptotics. The limit theory explicitly involves initial conditions, allows for drift in the system, is provided for single and multiple explosive regressors, and is feasible to implement in practice. Simulations show that double asymptotics deliver a good approximation to the finite sample distribution, with both finite sample and asymptotic distributions showing sensitivity to initial conditions. The methods are implemented in the US real estate market …

Inference In Continuous Systems With Mildly Explosive Regressors, Ye Chen, Peter C. B. Phillips, Jun Yu

Research Collection School Of Economics

New limit theory is developed for co-moving systems with explosive processes, connecting continuous and discrete time formulations. The theory uses double asymptotics with infill (as the sampling interval tends to zero) and large time span asymptotics. The limit theory explicitly involves initial conditions, allows for drift in the system, is provided for single and multiple explosive regressors, and is feasible to implement in practice. Simulations show that double asymptotics deliver a good approximation to the finite sample distribution, with both finite sample and asymptotic distributions showing sensitivity to initial conditions. The methods are implemented in the US real estate market …

Random Coefficient Continuous Systems: Testing For Extreme Sample Path Behaviour, Yubo Tao, Peter C. B. Phillips, Jun Yu

Research Collection School Of Economics

This paper studies a continuous time dynamic system with a random persistence parameter. The exact discrete time representation is obtained and related to several discrete time random coefficient models currently in the literature. The model distinguishes various forms of unstable and explosive behaviour according to specific regions of the parameter space that open up the potential for testing these forms of extreme behaviour. A two-stage approach that employs realized volatility is proposed for the continuous system estimation, asymptotic theory is developed, and test statistics to identify the different forms of extreme sample path behaviour are proposed. Simulations show that the …

Determining The Number Of Groups In Latent Panel Structures With An Application To Income And Democracy, Xun Lu, Liangjun Su

Research Collection School Of Economics

We consider a latent group panel structure as recently studied by Su, Shi, and Phillips (2014), where the number of groups is unknown and has to be determined empirically. We propose a testing procedure to determine the number of roups. Our test is a residualbased LM-type test. We show that after being appropriately standardized, our test is asymptotically normally distributed under the null hypothesis of a given number of groups and has power to detect deviations from the null. Monte Carlo simulations show that our test performs remarkably well in finite samples. We apply our method to study the effect …

Volatility Spillovers And Linkages In Asian Stock Markets, Hwee Kwan Chow-Tan

Research Collection School Of Economics

Diebold-Yilmaz spilloverindexes are computed for weekly return volatilities based on daily benchmarkstock indexes of US, UK and ten Asian countries. We found (i) the strengthening ofoverall volatility spillovers is not a temporary surge but persisted after thecrisis; (ii) the susceptibility ofindividual Asian stock markets to inward volatility transfers is linked to itsdegree of openness; and (iii) the Asian bourses are becoming more importantemitters of financial shocks since the crisis. Rolling regressions on volatilitylinkages reveal the relative dominance of the US over the Japanese and Chinesebourses, and the level of influence on Asian stock markets from the Chinesebourse has risen to …

Estimating Finite-Horizon Life-Cycle Models: A Quasi-Bayesian Approach, Xiaobin Liu

Research Collection School Of Economics

This paper proposes a quasi-Bayesian approach for structural parameters in finite-horizon life-cycle models. This approach circumvents the numerical evaluation of the gradient of the objective function and alleviates the local optimum problem. The asymptotic normality of the estimators with and without approximation errors is derived. The proposed estimators reach the semiparametric eciency bound in the general methods of moment (GMM) framework. Both the estimators and the corresponding asymptotic covariance are readily computable. The estimation procedure is easy to parallel so that the graphic processing unit (GPU) can be used to enhance the computational speed. The estimation procedure is illustrated using …

Strong Consistency Of Spectral Clustering For Stochastic Block Models, Liangjun Su, Wuyi Wang, Yichong Zhang

Research Collection School Of Economics

In this paper we prove the strong consistency of several methods based on thespectral clustering techniques that are widely used to study the communitydetection problem in stochastic block models (SBMs). We show that under someweak conditions on the minimal degree, the number of communities, and theeigenvalues of the probability block matrix, the K-means algorithm applied tothe Eigenvectors of the graph Laplacian associated with its first few largesteigenvalues can classify all individuals into the true community uniformlycorrectly almost surely. Extensions to both regularized spectral clustering anddegree-corrected SBMs are also considered. We illustrate the performance ofdifferent methods on simulated networks.

Specification Test For Spatial Autoregressive Models, Liangjun Su, Xi Qu

Research Collection School Of Economics

This article considers a simple test for the correct specification of linear spatial autoregressive models, assuming that the choice of the weight matrix Wn is true. We derive the limiting distributions of the test under the null hypothesis of correct specification and a sequence of local alternatives. We show that the test is free of nuisance parameters asymptotically under the null and prove the consistency of our test. To improve the finite sample performance of our test, we also propose a residual-based wild bootstrap and justify its asymptotic validity. We conduct a small set of Monte Carlo simulations to investigate …