Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Finance (85)
- Business (41)
- Asian Studies (37)
- International and Area Studies (37)
- Economic Theory (30)
-
- Medicine and Health Sciences (24)
- Finance and Financial Management (23)
- Physical Sciences and Mathematics (21)
- Statistics and Probability (18)
- Behavioral Economics (12)
- Macroeconomics (11)
- Real Estate (10)
- Health Economics (7)
- Applied Statistics (5)
- Portfolio and Security Analysis (5)
- Public Affairs, Public Policy and Public Administration (5)
- Industrial Organization (4)
- Environmental Sciences (3)
- Growth and Development (3)
- International Economics (3)
- Labor Economics (3)
- Public Health (3)
- Statistical Models (3)
- Computer Sciences (2)
- Economic Policy (2)
- Education (2)
- Medical Sciences (2)
- Keyword
-
- Specification test (28)
- Fixed effects (24)
- Bootstrap (23)
- Panel data (22)
- High-frequency data (16)
-
- Heterogeneity (15)
- Realized volatility (15)
- Dynamic panel (14)
- Endogeneity (14)
- Interactive fixed effects (14)
- Autoregression (13)
- Empirical likelihood (13)
- Long memory (13)
- Markov chain Monte Carlo (13)
- Nonstationarity (13)
- Structural change (13)
- Bias reduction (12)
- Cointegration (12)
- Semimartingale (12)
- Spatial dependence (12)
- Bias (11)
- Consistency (11)
- Factor model (11)
- Heteroskedasticity (11)
- Maximum likelihood (11)
- Nonparametric regression (11)
- Box-Cox transformation (10)
- Explosive process (10)
- Latent variable models (10)
- Local to unity (10)
- Publication Year
- Publication
- Publication Type
Articles 601 - 630 of 828
Full-Text Articles in Econometrics
A Paradox Of Inconsistent Parametric And Consistent Nonparametric Regression, Peter C. B. Phillips, Liangjun Su
A Paradox Of Inconsistent Parametric And Consistent Nonparametric Regression, Peter C. B. Phillips, Liangjun Su
Research Collection School Of Economics
This paper explores a paradox discovered in recent work by Phillips and Su (2009). That paper gave an example in which nonparametric regression is consistent whereas parametric regression is inconsistent even when the true regression functional form is known and used in regression. This appears to be a paradox, as knowing the true functional form should not in general be detrimental in regression. In the present case, local regression methods turn out to have a distinct advantage because of endogeneity in the regressor. The paradox arises because additional correct information is not necessarily advantageous when information is incomplete. In the …
Using High-Frequency Transaction Data To Estimate The Probability Of Informed Trading, Anthony S. Tay, Christopher Ting, Yiu Kuen Tse, Mitchell Warachka
Using High-Frequency Transaction Data To Estimate The Probability Of Informed Trading, Anthony S. Tay, Christopher Ting, Yiu Kuen Tse, Mitchell Warachka
Research Collection School Of Economics
This paper applies the asymmetric autoregressive conditional duration (AACD) model of Bauwens and Giot (2003) to estimate the probability of informed trading (PIN) using irregularly spaced transaction data. We model trade direction (buy versus sell orders) and the duration between trades jointly. Unlike the Easley, Hvidkjaer, and O'Hara (2002) approach, which uses the aggregate numbers of daily buy and sell orders to estimate PIN, our methodology allows for interactions between consecutive buy-sell orders and accounts for the duration between trades and the volume of trade. We extend the Easley–Hvidkjaer–O'Hara framework by allowing the probabilities of good news and bad news …
Limit Theory For Dating The Origination And Collapse Of Mildly Explosive Periods In Time Series Data, Jun Yu, Peter C. B. Phillips
Limit Theory For Dating The Origination And Collapse Of Mildly Explosive Periods In Time Series Data, Jun Yu, Peter C. B. Phillips
Research Collection School Of Economics
Some limit theory is developed for estimators suggested in Phillips, Wu and Yu (2009) for dating bubble pheonoma in time series data. The models involve mildly explosive autoregressions and the tests rely on right sided recursive unit root tests. The estimates locate the origination and collapse dates of bubbles involving mildly explosive episodes set within longer periods where the data evolve as a stochastic trend. The dating estimators are shown to be consistent under mild regularity conditions on the process. Some simulation evidence on the performance of the estimators is reported. The proposed method works well in finite samples and …
Limit Theory For Cointegrated Systems With Moderately Integrated And Moderately Explosive Regressors, Tassos Magdalinos, Peter C. B. Phillips
Limit Theory For Cointegrated Systems With Moderately Integrated And Moderately Explosive Regressors, Tassos Magdalinos, Peter C. B. Phillips
Research Collection School Of Economics
An asymptotic theory is developed for multivariate regression in cointegrated systems whose variables are moderately integrated or moderately explosive in the sense that they have autoregressive roots of the form rho(ni) = 1 + c(i)/n(alpha), involving moderate deviations from unity when alpha is an element of (0, 1) and c(i) is an element of R are constant parameters. When the data are moderately integrated in the stationary direction (with c(i) < 0), it is shown that least squares regression is consistent and asymptotically normal but suffers from significant bias, related to simultaneous equations bias. In the moderately explosive case (where c(i) > 0) the limit theory is mixed normal with Cauchy-type tail behavior, and the rate of convergence is explosive, as in the case of a moderately explosive scalar autoregression (Phillips and …
Testing Conditional Uncorrelatedness, Liangjun Su, Aman Ullah
Testing Conditional Uncorrelatedness, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We propose a nonparametric test for conditional uncorrelatedness in multiple-equation models such as seemingly unrelated regressions (SURs), multivariate volatility models, and vector autoregressions (VARs). Under the null hypothesis of conditional uncorrelatedness, the test statistic converges to the standard normal distribution asymptotically. We also study the local power property of the test. Simulation shows that the test behaves quite well in finite samples.
Semiparametric Cointegrating Rank Selection, Xu Cheng, Peter C. B. Phillips
Semiparametric Cointegrating Rank Selection, Xu Cheng, Peter C. B. Phillips
Research Collection School Of Economics
Some convenient limit properties of usual information criteria are given for cointegrating rank selection. Allowing for a non-parametric short memory component and using a reduced rank regression with only a single lag, standard information criteria are shown to be weakly consistent in the choice of cointegrating rank provided the penalty coefficient C(n) -> infinity and C(n)/n -> 0 as n -> 8. The limit distribution of the AIC criterion, which is inconsistent, is also obtained. The analysis provides a general limit theory for semiparametric reduced rank regression under weakly dependent errors. The method does not require the specification of a …
Asymptotics And Bootstrap For Transformed Panel Data Regressions, Liangjun Su, Zhenlin Yang
Asymptotics And Bootstrap For Transformed Panel Data Regressions, Liangjun Su, Zhenlin Yang
Research Collection School Of Economics
This paper investigates the asymptotic properties of quasi-maximum likelihood estimators for transformed random effects models where both the response and (some of) the covariates are subject to transformations for inducing normality, flexible functional form, homoscedasticity, and simple model structure. We develop a quasi maximum likelihood-type procedure for model estimation and inference. We prove the consistency and asymptotic normality of the parameter estimates, and propose a simple bootstrap procedure that leads to a robust estimate of the variance-covariance matrix. Monte Carlo results reveal that these estimates perform well in finite samples, and that the gains by using bootstrap procedure for inference …
Semiparametric Prevalence Estimation From A Two-Phase Survey, Denis H. Y. Leung, J Qin
Semiparametric Prevalence Estimation From A Two-Phase Survey, Denis H. Y. Leung, J Qin
Research Collection School Of Economics
This paper studies a semi-parametric method for estimating the prevalence of a binary outcome using a two-phase survey. The motivation for a two-phase survey is, due to time, money and ethical considerations, it is impossible to carry out comprehensive evaluation on all subjects in a large random sample of the population. Rather, a relatively inexpensive "screening test" is given to all subjects in the random sample and only individuals more likely to have a positive outcome (cases) will be selected for a further "gold standard" test to verify the outcome. Therefore, individuals with verified outcome form a non-random sample from …
Markov Switching Var Model Of Speculative Pressure: An Application To The Asian Financial Crisis, Gregorio Iii Alfredo Vargas
Markov Switching Var Model Of Speculative Pressure: An Application To The Asian Financial Crisis, Gregorio Iii Alfredo Vargas
Dissertations and Theses Collection (Open Access)
Markov switching models with time-varying transition probabilities address the limitations of the earlier methods in the early warning system literature on currency crises. Most of the Markov switching models in the literature are largely based on univariate models of exchange rate fluctuations. In this thesis, the components of the index of speculative pressure are modeled using the Markov Switching VAR with time-varying transition probabilities of Martinez Peria (2002). Two approaches, both of which are derived from this model, are taken to determine the probability of a currency crisis: the probability of a turbulent regime and the expected value of the …
Multivariate Garch Models For The Greater China Stock Markets, Xiaojun Song
Multivariate Garch Models For The Greater China Stock Markets, Xiaojun Song
Dissertations and Theses Collection (Open Access)
This paper reviews the commonly used multivariate GARCH models and uses the daily data of the four Greater China region stock markets, namely Hongkong, Shanghai,Shenzhen, and Singapore, and data of Japan as one ex-ogenous variable to investigate the volatility and shocks spillover behavior and to establish the market linkage among the four markets. We find that the volatility spillover between Shanghai and Shenzhen is obvious and correlation contagion is detected. Conditional variance and conditional correlations are time varying and dynamic which conforms to the arguments in most of the literature. Shanghai and Shenzhen present a very high correlation level during …
A Robust Lm Test For Spatial Error Components, Zhenlin Yang
A Robust Lm Test For Spatial Error Components, Zhenlin Yang
Research Collection School Of Economics
This paper presents a modified LM test of spatial error components, which is shown to be robust against distributional misspecifications and spatial layouts. The proposed test differs from the LM test of Anselin (2001) by a term in the denominators of the test statistics. This term disappears when either the errors are normal, or the variance of the diagonal elements of the product of spatial weights matrix and its transpose is zero or approaches to zero as sample size goes large. When neither is true, as is often the case in practice, the effect of this term can be significant …
A Centered Index Of Spatial Concentration: Axiomatic Approach With An Application To Population And Capital Cities, Filipe R. Campante, Quoc-Anh Do
A Centered Index Of Spatial Concentration: Axiomatic Approach With An Application To Population And Capital Cities, Filipe R. Campante, Quoc-Anh Do
Research Collection School Of Economics
We construct an axiomatic index of spatial concentration around a center or capital point of interest, a concept with wide applicability from urban economics, economic geography and trade, to political economy and industrial organization. We propose basic axioms (decomposability and monotonicity) and refinement axioms (order preservation, convexity, and local monotonicity) for how the index should respond to changes in the underlying distribution. We obtain a unique class of functions satisfying all these properties, defined over any n-dimensional Euclidian space: the sum of a decreasing, isoelastic function of individual distances to the capital point of interest, with specific boundaries for the …
Maximum Likelihood And Gaussian Estimation Of Continuous Time Models In Finance, Peter C. B. Phillips, Jun Yu
Maximum Likelihood And Gaussian Estimation Of Continuous Time Models In Finance, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
This paper overviews maximum likelihood and Gaussian methods of estimating continuous time models used in finance. Since the exact likelihood can be constructed only in special cases, much attention has been devoted to the development of methods designed to approximate the likelihood. These approaches range from crude Euler-type approximations and higher order stochastic Taylor series expansions to more complex polynomial-based expansions and infill approximations to the likelihood based on a continuous time data record. The methods are discussed, their properties are outlined and their relative finite sample performance compared in a simulation experiment with the nonlinear CIR diffusion model, which …
Future Fiscal And Budgetary Shocks, Hian Teck Hoon, Edmund S. Phelps
Future Fiscal And Budgetary Shocks, Hian Teck Hoon, Edmund S. Phelps
Research Collection School Of Economics
We study the effects of future tax and budgetary shocks in a non-monetary and possibly non-Ricardian economy. An (unanticipated) temporary labor tax cut to be effective on a given future date—a delayed “debt bomb”—causes at once a drop in the (unit) value placed on the firms' business asset, the customer, with the result that share prices, the hourly wage, and employment drop in tandem. This paradox of reduced activity through announcement of future “stimulus” does not hinge on an upward jump of long interest rates. A future tax-rate cut lacking a “sunset” provision has the same negative effects.
Testing For Parameter Stability In Quantile Regression Models, Liangjun Su, Zhijie Xiao
Testing For Parameter Stability In Quantile Regression Models, Liangjun Su, Zhijie Xiao
Research Collection School Of Economics
We propose a test for structural change of conditional distribution in dynamic regression models. The test is constructed based on time series regression quantile estimates and complements conventional parameter instability tests in least-square type regression models. Asymptotic distribution for our test under the null hypothesis is derived.
Improving Semiparametric Estimation By Using Surrogate Data, Song Xi Chen, Leung, Denis H. Y., Jin Qin
Improving Semiparametric Estimation By Using Surrogate Data, Song Xi Chen, Leung, Denis H. Y., Jin Qin
Research Collection School Of Economics
The paper considers estimating a parameter beta that defines an estimating function U(y, x, beta) for an outcome variable y and its covariate x when the outcome is missing in some of the observations. We assume that, in addition to the outcome and the covariate, a surrogate outcome is available in every observation. The efficiency of existing estimators for beta depends critically on correctly specifying the conditional expectation of U given the surrogate and the covariate. When the conditional expectation is not correctly specified, which is the most likely scenario in practice, the efficiency of estimation can be severely compromised …
A Nonparametric Hellinger Metric Test For Conditional Independence, Liangjun Su, Halbert White
A Nonparametric Hellinger Metric Test For Conditional Independence, Liangjun Su, Halbert White
Research Collection School Of Economics
We propose a nonparametric test of conditional independence based on the weighted Hellinger distance between the two conditional densities, f(y|x,z) and f(y|x), which is identically zero under the null. We use the functional delta method to expand the test statistic around the population value and establish asymptotic normality under β-mixing conditions. We show that the test is consistent and has power against alternatives at distance n−1/2h−d/4. The cases for which not all random variables of interest are continuously valued or observable are also discussed. Monte Carlo simulation results indicate that the test behaves reasonably well in …
On The Evaluation Of The Joint Distribution Of Order Statistics, Koon Shing Kwong, Yiu Man Chan
On The Evaluation Of The Joint Distribution Of Order Statistics, Koon Shing Kwong, Yiu Man Chan
Research Collection School Of Economics
Dunnett and Tamhane [Dunnett, C.W., Tamhane, A.C., 1992. A step-up multiple test procedure. J. Amer. Statist. Assoc. 87, 162-170.] proposed a step-up procedure for comparing k treatments with a control and showed that the step-up procedure is more powerful than its counterpart single step and step-down procedures. Since then, several modified step-up procedures have been suggested to deal with different testing environments. In order to establish those step-up procedures, it is necessary to derive approaches for evaluating the joint distribution of the order statistics. In some cases, experimenters may have difficulty in applying those step-up procedures in multiple hypothesis testing …
Limit Theory For Explosively Cointegrated Systems, Peter C. B. Phillips, Tassos Magdalinos
Limit Theory For Explosively Cointegrated Systems, Peter C. B. Phillips, Tassos Magdalinos
Research Collection School Of Economics
A limit theory is developed for multivariate regression in an explosive cointegrated system. The asymptotic behavior of the least squares estimator of the cointegrating coefficients is found to depend upon the precise relationship between the explosive regressors. When the eigenvalues of the autoregressive matrix Θ are distinct, the centered least squares estimator has an exponential Θn rate of convergence and a mixed normal limit distribution. No central limit theory is applicable here, and Gaussian innovations are assumed. On the other hand, when some regressors exhibit common explosive behavior, a different mixed normal limiting distribution is derived with rate of convergence …
Regression Asymptotics Using Martingale Convergence Methods, Rustam Ibragimov, Peter C. B. Phillips
Regression Asymptotics Using Martingale Convergence Methods, Rustam Ibragimov, Peter C. B. Phillips
Research Collection School Of Economics
Weak convergence of partial sums and multilinear forms in independent random variables and linear processes and their nonlinear analogues to stochastic integrals now plays a major role in nonstationary time series and has been central to the development of unit root econometrics. The present paper develops a new and conceptually simple method for obtaining such forms of convergence. The method relies on the fact that the econometric quantities of interest involve discrete time martingales or semimartingales and shows how in the limit these quantities become continuous martingales and semimartingales. The limit theory itself uses very general convergence results for semimartingales …
Nonparametric Prewhitening Estimators For Conditional Quantiles, Liangjun Su, Aman Ullah
Nonparametric Prewhitening Estimators For Conditional Quantiles, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We define a nonparametric prewhitening method for estimating conditional quantiles based on local linear quantile regression. We characterize the bias, variance and asymptotic normality of the proposed estimator. Under weak conditions our estimator can achieve bias reduction and have the same variance as the local linear quantile estimators. A small set of Monte Carlo simulations is carried out to illustrate the performance of our estimators. An application to US gross domestic product data demonstrates the usefulness of our methodology.
A Semiparametric Stochastic Volatility Model, Jun Yu
A Semiparametric Stochastic Volatility Model, Jun Yu
Research Collection School Of Economics
This paper examines how volatility responds to return news in the context of stochastic volatility (SV) using a nonparametric method. The correlation structure in the classical leverage SV model is generalized based on a linear spline. In the new model the correlation between the return innovation and volatility innovation is dependent on the type of news arrived to the market. Theoretical properties of the proposed model are examined. A simulation-based maximum likelihood method is developed to estimate the new model. Simulations show that the estimation method provides reliable parameter estimates. The new model is fitted to daily and weekly data …
Time-Varying Incentives In The Mutual Fund Industry, Jacques Olivier, Anthony S. Tay
Time-Varying Incentives In The Mutual Fund Industry, Jacques Olivier, Anthony S. Tay
Research Collection School Of Economics
This paper re-examines the incentives of mutual fund managers arising from investor flows. We provide evidence that the convexity of the flow-performance relationship varies with economic activity. We show that the effect is economically large and is not driven by abnormal years. We test two possible channels through which this pattern may arise. We investigate implications of the timevarying convexity for the incentives of managers to alter strategically the risk of their portfolios. We provide evidence that poor mid-year performers increase the risk of the portfolio only when economic activity is strong. Finally, we briefly discuss some methodological implications.
Inference For General Parametric Functions In Box-Cox-Type Transformation Models, Zhenlin Yang, Eden Ka-Ho Wu, Anthony F. Desmond
Inference For General Parametric Functions In Box-Cox-Type Transformation Models, Zhenlin Yang, Eden Ka-Ho Wu, Anthony F. Desmond
Research Collection School Of Economics
The authors propose a simple but general method of inference for a parametric function of the Box-Cox-type transformation model. Their approach is built upon the classical normal theory but takes parameter estimation into account. It quickly leads to test statistics and confidence intervals for a linear combination of scaled or unscaled regression coefficients, as well as for the survivor function and marginal effects on the median or other quantile functions of an original response. The authors show through simulations that the finite-sample performance of their method is often superior to the delta method, and that their approach is robust to …
Gaussian Inference In Ar(1) Time Series With Or Without A Unit Root, Peter C. B. Phillips, Chirok Han
Gaussian Inference In Ar(1) Time Series With Or Without A Unit Root, Peter C. B. Phillips, Chirok Han
Research Collection School Of Economics
This paper introduces a simple first-difference-based approach to estimation and inference for the AR(1) model. The estimates have virtually no finite-sample bias and are not sensitive to initial conditions, and the approach has the unusual advantage that a Gaussian central limit theory applies and is continuous as the autoregressive coefficient passes through unity with a uniform rate of convergence. En route, a useful central limit theorem (CLT) for sample covariances of linear processes is given, following Phillips and Solo (1992, Annals of Statistics, 20, 971–1001). The approach also has useful extensions to dynamic panels.
Local Polynomial Estimation Of Nonparametric Simultaneous Equations Models, Liangjun Su, Aman Ullah
Local Polynomial Estimation Of Nonparametric Simultaneous Equations Models, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We define a new procedure for consistent estimation of nonparametric simultaneous equations models under the conditional mean independence restriction of Newey et al. [1999. Nonparametric estimation of triangular simultaneous equation models. Econometrica 67, 565-603]. It is based upon local polynomial regression and marginal integration techniques. We establish the asymptotic distribution of our estimator under weak data dependence conditions. Simulation evidence suggests that our estimator may significantly outperform the estimators of Pinkse [2000. Nonparametric two-step regression estimation when regressors and errors are dependent. Canadian Journal of Statistics 28, 289-300] and Newey and Powell [2003. Instrumental variable estimation of nonparametric models. Econometrica …
Testing Intergroup Concordance In Ranking Experiments With Two Groups Of Judges, Dawn J. Dekle, Leung, Denis H. Y., Min Zhu
Testing Intergroup Concordance In Ranking Experiments With Two Groups Of Judges, Dawn J. Dekle, Leung, Denis H. Y., Min Zhu
Research Collection School Of Economics
Across many areas of psychology, concordance is commonly used to measure the (intragroup) agreement in ranking a number of items by a group of judges. Sometimes, however, the judges come from multiple groups, and in those situations, the interest is to measure the concordance between groups, under the assumption that there is some within-group concordance. In this investigation, existing methods are compared under a variety of scenarios. Permutation theory is used to calculate the error rates and the power of the methods. Missing data situations are also studied. The results indicate that the performance of the methods depend on (a) …
Asymptotic Variance And Extensions Of A Denisty-Weighted-Response Semiparametric Estimator, Myoung-Jae Lee, Fali Huang, Young-Sook Kim
Asymptotic Variance And Extensions Of A Denisty-Weighted-Response Semiparametric Estimator, Myoung-Jae Lee, Fali Huang, Young-Sook Kim
Research Collection School Of Economics
Building on some early works, Lewbel (2000) proposed estimators for binary and ordered discrete response models with endogenous regressors. These estimators have been extended for panel data and for truncated and censored models by later papers. The estimators are particularly innovative in that the latent linear regression functions are pulled out of the nonlinear limited dependent variable models, which are then treated as if they were the usual linear models. But understanding the estimators and their applications have been “hampered” by less-than-ideal expositions and assumptions. For this problem, this short note reviews the estimators and makes the following three points. …
Testing Structural Change In Time-Series Nonparametric Regression Models, Liangjun Su, Zhijie Xiao
Testing Structural Change In Time-Series Nonparametric Regression Models, Liangjun Su, Zhijie Xiao
Research Collection School Of Economics
We propose a CUSUM type of test for structural change in dynamic nonparametric regression models. It is based upon the cumulative sums of weighted residuals from a single nonparametric regression and complements the conventional parameter instability tests in parametric models. We derive the limiting distributions of the test under both the null hypothesis and sequences of local alternatives. A boot-strap procedure is also proposed and its validity is justified. Finally, simulation experiments are conducted to investigate the finite sample properties of our test.
Mapping The Discipline Of The Olympic Games An Author-Cocitation Analysis, Peter Warning, Rosie Ching, Kristine Toohey
Mapping The Discipline Of The Olympic Games An Author-Cocitation Analysis, Peter Warning, Rosie Ching, Kristine Toohey
Research Collection School Of Economics
The authors conducted an author cocitation analysis on prominent authors writing about the Olympics during the 1990s. Author cocitation is an established bibliometric technique that can be used to measure the relative similarities of topics written about by the cited authors. This enables a visual representation of the “intellectual space” of the discipline, in this case the Olympics, to be created for the period under review. So core and peripheral research areas are identified, along with their major contributors. The representation appears as a two-dimensional cluster-enhanced map. Subject expertise was then applied to the results to place labels on the …