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Articles 1 - 25 of 25
Full-Text Articles in Social and Behavioral Sciences
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 …
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 …
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 …
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 …
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.
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 …
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.
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 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.
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 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) …
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 …
Optimal Collusion With Internal Contracting, Gea Myoung Lee
Optimal Collusion With Internal Contracting, Gea Myoung Lee
Research Collection School Of Economics
In this paper, we develop a model of collusion in which two firms play an infinitelyrepeated Bertrand game when each firm has a privately-informed agent. The colluding firms, fixing prices, allocate market shares based on the agent’s information as to cost types. We emphasize that the presence of privately-informed agents may provide firms with a strategic opportunity to exploit an interaction between internal contracting and market-sharing arrangement: the contracts with agents may be used to induce firms’ truthful communication in their collusion, and collusive market-share allocation may act to reduce the agents’ information rents.
Hong Kong's Money: The History, Logic And Operation Of The Currency Peg, Hwee Kwan Chow
Hong Kong's Money: The History, Logic And Operation Of The Currency Peg, Hwee Kwan Chow
Research Collection School Of Economics
No abstract provided.
Unit Root Model Selection, Peter C. B. Phillips
Unit Root Model Selection, Peter C. B. Phillips
Research Collection School Of Economics
Some limit properties for information based model selection criteria are given in the context of unit root evaluation and various assumptions about initial conditions. Allowing for a nonparametric short memory component, standard information criteria are shown to be weakly consistent for a unit root provided the penalty coefficient Cn?? and Cn/n?0 as n??. Strong consistency holds when Cn/(log logn)3?? under conventional assumptions on initial conditions and under a slightly stronger condition when initial conditions are infinitely distant in the unit root model. The limit distribution of the AIC criterion is obtained.
Rational And Boundedly Rational Behavior In Sender-Receiver Games, Massimiliano Landi, Domenico Colucci
Rational And Boundedly Rational Behavior In Sender-Receiver Games, Massimiliano Landi, Domenico Colucci
Research Collection School Of Economics
The authors investigate the strategic rationale behind the message sent by Osama bin Laden on the eve of the 2004 U.S. Presidential elections. They model this situation as a signaling game in which a population of receivers takes a binary choice, the outcome is decided by majority rule, sender and receivers have conflicting interests, and there is uncertainty about both players’ degree of rationality. They characterize the structure of the sequential equilibria of the game as a function of the parameters governing the uncertainty and find that in all pure strategy equilibria, the outcome most preferred by the rational sender …
Optimal Bandwidth Selection In Heteroskedasticity-Autocorrelation Robust Testing, Yixiao Sun, Peter C. B. Phillips, Sainan Jin
Optimal Bandwidth Selection In Heteroskedasticity-Autocorrelation Robust Testing, Yixiao Sun, Peter C. B. Phillips, Sainan Jin
Research Collection School Of Economics
This paper considers studentized tests in time series regressions with nonparametrically autocorrelated errors. The studentization is based on robust standard errors with truncation lag M = bT for some constant b ∈ (0, 1] and sample size T. It is shown that the nonstandard fixed-b limit distributions of such nonparametrically studentized tests provide more accurate approximations to the finite sample distributions than the standard small-b limit distribution. We further show that, for typical economic time series, the optimal bandwidth that minimizes a weighted average of type I and type II errors is larger by an order of magnitude than the …
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C. B. Phillips
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C. B. Phillips
Research Collection School Of Economics
Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution or combinations of the two. This paper develops kernel-based estimators of the residual variances and associated adaptive least squares (ALS) estimators of the autoregressive coefficients. Simulations show that efficiency gains are achieved by the adaptive procedure.
Refined Inference On Long Memory In Realized Volatility, Peter C. B. Phillips, Offer Lieberman
Refined Inference On Long Memory In Realized Volatility, Peter C. B. Phillips, Offer Lieberman
Research Collection School Of Economics
There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the accumulative process underlying realized volatility. The article also uses results in Lieberman and Phillips (2004, 2005) to refine statistical inference about by higher order theory. Standard asymptotic theory has an error rate for error rejection probabilities, and the theory used here refines the approximation to an error rate of. The new formula is independent …