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Articles 601 - 630 of 771
Full-Text Articles in Econometrics
Direction-Of-Change Forecasts For Asian Equity Markets Based On Conditional Variance, Skewness And Kurtosis Dynamics: International Evidence, Peter F. Christoffersen, Francis X. Diebold, Robert S. Mariano, Anthony S. Tay, Yiu Kuen Tse
Direction-Of-Change Forecasts For Asian Equity Markets Based On Conditional Variance, Skewness And Kurtosis Dynamics: International Evidence, Peter F. Christoffersen, Francis X. Diebold, Robert S. Mariano, Anthony S. Tay, Yiu Kuen Tse
Research Collection School Of Economics
Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.
Indirect Inference For Dynamic Panel Models, Jun Yu
Indirect Inference For Dynamic Panel Models, Jun Yu
Research Collection School Of Economics
It is well-known that maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size (T) and large cross section sample size (N) asymptotics. The estimation bias is particularly relevant in practical applications when T is small and the autoregressive parameter is close to unity. The present paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference (Gouriéroux et al., 1993), shows unbiasedness and analyzes efficiency. The method is implemented in a simple linear dynamic panel model, but has wider …
Instrumental Variable Quantile Estimation Of Spatial Autoregressive Models, Zhenlin Yang
Instrumental Variable Quantile Estimation Of Spatial Autoregressive Models, Zhenlin Yang
Research Collection School Of Economics
We propose an instrumental variable quantile regression (IVQR) estimator for spatial autoregressive (SAR) models. Like the GMM estimators of Lin and Lee (2006) and Kelejian and Prucha (2006), the IVQR estimator is robust against heteroscedasticity. Unlike the GMM estimators, the IVQR estimator is also robust against outliers and requires weaker moment conditions. More importantly, it allows us to characterize the heterogeneous impact of variables on different points (quantiles) of a response distribution. We derive the limiting distribution of the new estimator. Simulation results show that the new estimator performs well in finite samples at various quantile points. In the special …
Unit Root Log Periodogram Regression, Peter C. B. Phillips
Unit Root Log Periodogram Regression, Peter C. B. Phillips
Research Collection School Of Economics
Log periodogram (LP) regression is shown to be consistent and to have a mixed normal limit distribution when the memory parameter d=1. Gaussian errors are not required. The proof relies on a new result showing that asymptotically infinite collections of discrete Fourier transforms (dft's) of a short memory process at the fundamental frequencies in the vicinity of the origin can be treated as asymptotically independent normal variates, provided one does not include too many dft's in the collection.
Bayesian Analysis Of Dsge Models, Sungbae An, Frank Schorfheide
Bayesian Analysis Of Dsge Models, Sungbae An, Frank Schorfheide
Research Collection School Of Economics
This paper reviews Bayesian methods that have been developed in recent years to estimate and evaluate dynamic stochastic general equilibrium (DSGE) models. We consider the estimation of linearized DSGE models, the evaluation of models based on Bayesian model checking, posterior odds comparisons, and comparisons to vector autoregressions, as well as the non-linear estimation based on a second-order accurate model solution. These methods are applied to data generated from correctly specified and misspecified linearized DSGE models and a DSGE model that was solved with a second-order perturbation method.
Modelling Spatial Dependence And Social Interactions, Zhenlin Yang
Modelling Spatial Dependence And Social Interactions, Zhenlin Yang
Research Collection School Of Economics
Spatial dependence or social interaction among economic agents or social actors, such as neighbourhood effects, copycatting, and peer group effects, has recently received increased attention from regional scientists, economists, econometricians, and statisticians.
A Unified Confidence Interval For Reliability-Related Quantities Of Two-Parameter Weibull Distribution, Zhenlin Yang, Min Xie, Augustine C.M. Wong
A Unified Confidence Interval For Reliability-Related Quantities Of Two-Parameter Weibull Distribution, Zhenlin Yang, Min Xie, Augustine C.M. Wong
Research Collection School Of Economics
Statistical inference methods for the Weibull parameters and their functions usually depend on extensive tables, and hence are rather inconvenient for the practical applications. In this paper, we propose a general method for constructing confidence intervals for the Weibull parameters and their functions, which eliminates the need for the extensive tables. The method is applied to obtain confidence intervals for the scale parameter, the mean-time-to-failure, the percentile function, and the reliability function. Monte-Carlo simulation shows that these intervals possess excellent finite sample properties, having coverage probabilities very close to their nominal levels, irrespective of the sample size and the degree …
Global And Regional Sources Of Risk In Equity Markets: Evidence From Factor Models With Time-Varying Conditional Skewness, Aamir R. Hashmi, Anthony S. Tay
Global And Regional Sources Of Risk In Equity Markets: Evidence From Factor Models With Time-Varying Conditional Skewness, Aamir R. Hashmi, Anthony S. Tay
Research Collection School Of Economics
We examine the influence of global and regional factors on the conditional distribution of stock returns from six Asian markets, using factor models in which unexpected returns comprise global, regional and local shocks. The models allow for conditional heteroskedasticity and time-varying conditional skewness, and are used to measure mean, variance, and skewness spillovers. We find that incorporating time-varying conditional skewness improves the fit of our spillover models, and can alter measurements of variance spillovers. However, time-varying conditional skewness is mostly a local phenomenon; with exceptions, there is little spillover in skewness from global and regional factors.
A Simple Approach To The Parametric Estimation Of Potentially Nonstationary Diffusions, Federico Bandi, Peter C. B. Phillips
A Simple Approach To The Parametric Estimation Of Potentially Nonstationary Diffusions, Federico Bandi, Peter C. B. Phillips
Research Collection School Of Economics
A simple and robust approach is proposed for the parametric estimation of scalar homogeneous stochastic differential equations. We specify a parametric class of diffusions and estimate the parameters of interest by minimizing criteria based on the integrated squared difference between kernel estimates of the drift and diffusion functions and their parametric counterparts. The procedure does not require simulations or approximations to the true transition density and has the simplicity of standard nonlinear least-squares methods in discrete time. A complete asymptotic theory for the parametric estimates is developed. The limit theory relies on infill and long span asymptotics and is robust …
Simulation-Based Estimation Of Contingent-Claims Prices, Jun Yu
Simulation-Based Estimation Of Contingent-Claims Prices, Jun Yu
Research Collection School Of Economics
A new methodology is proposed to estimate theoretical prices of financial contingent-claims whose values are dependent on some other underlying financial assets. In the literature the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but is not necessarily the best method in finite samples. The present paper proposes instead a simulation-based method that improves the finite sample performance of the ML estimator while maintaining its good asymptotic properties. The methods are implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond pricing model, but have wider applicability. Monte Carlo …
Long Run Variance Estimation And Robust Regression Testing Using Sharp Origin Kernels With No Truncation, Peter C. B. Phillips, Yixiao Sun, Sainan Jin
Long Run Variance Estimation And Robust Regression Testing Using Sharp Origin Kernels With No Truncation, Peter C. B. Phillips, Yixiao Sun, Sainan Jin
Research Collection School Of Economics
A new family of kernels is suggested for use in long run variance (LRV) estimation and robust regression testing. The kernels are constructed by taking powers of the Bartlett kernel and are intended to be used with no truncation (or bandwidth) parameter. As the power parameter ([rho]) increases, the kernels become very sharp at the origin and increasingly downweight values away from the origin, thereby achieving effects similar to a bandwidth parameter. Sharp origin kernels can be used in regression testing in much the same way as conventional kernels with no truncation, as suggested in the work of Kiefer and …
Bias In Dynamic Panel Estimation With Fixed Effects, Incidental Trends And Cross Section Dependence, Peter C. B. Phillips, Donggyu Sul
Bias In Dynamic Panel Estimation With Fixed Effects, Incidental Trends And Cross Section Dependence, Peter C. B. Phillips, Donggyu Sul
Research Collection School Of Economics
Explicit asymptotic bias formulae are given for dynamic panel regression estimators as the cross section sample size N --> ∞. The results extend earlier work by Nickell [1981. Biases in dynamic models with fixed effects. Econometrica 49, 1417-1426] and later authors in several directions that are relevant for practical work, including models with unit roots, deterministic trends, predetermined and exogenous regressors, and errors that may be cross sectionally dependent. The asymptotic bias is found to be so large when incidental linear trends are fitted and the time series sample size is small that it changes the sign of the autoregressive …
Monotonicity Conditions And Inequality Imputation For Sample-Selection And Non-Response Problems, Myoung-Jae Lee
Monotonicity Conditions And Inequality Imputation For Sample-Selection And Non-Response Problems, Myoung-Jae Lee
Research Collection School Of Economics
Under a sample selection or non-response problem, where a response variable y is observed only when a condition δ = 1 is met, the identified mean E(y|δ = 1) is not equal to the desired mean E(y). But the monotonicity condition E(y|δ = 1) ≤ E(y|δ = 0) yields an informative bound E(y|δ = 1) ≤ E(y), which is enough for certain inferences. For example, in a majority voting with δ being the vote-turnout, it is enough to know if E(y) > 0.5 or not, for which E(y|δ = 1) > 0.5 is sufficient under the monotonicity. The main question is then …
Open Vs Sealed Bid Auctions: Testing For Revenue Equivalence Under Singapore's Vehicle Quota System, Roberto S. Mariano, Winston T. H. Koh, Yiu Kuen Tse
Open Vs Sealed Bid Auctions: Testing For Revenue Equivalence Under Singapore's Vehicle Quota System, Roberto S. Mariano, Winston T. H. Koh, Yiu Kuen Tse
Research Collection School Of Economics
Using data from the auction of vehicle quota licenses in Singapore, we study if revenue equivalence holds when the auction format was switched from a sealed-bid format (May 1990 to June 2001) to an open bidding format since July 2001. Our econometric analysis indicates the change in auction format led to a change in bidding behavior. On average, the quota license premium under the open bidding format is about US$1000 (about 7.5% of the Category E license price in June 2001) lower, compared to the forecast level that would have prevailed if there had been no change in the auction …
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
Maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size and large cross section sample size asymptotics. This paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference, shows unbiasedness and analyzes efficiency. Monte Carlo studies show that our procedure achieves substantial bias reductions with only mild increases in variance, thereby substantially reducing root mean square errors. The method is compared with certain consistent estimators and is shown to have superior finite sample properties to the generalized method of …
Limit Theory For Moderate Deviations From A Unit Root Under Weak Dependence, Peter C. B. Phillips, Tassos Magadalinos
Limit Theory For Moderate Deviations From A Unit Root Under Weak Dependence, Peter C. B. Phillips, Tassos Magadalinos
Research Collection School Of Economics
An asymptotic theory is given for autoregressive time series with weakly dependent innovations and a root of the form rho_{n} = 1+c/n^{alpha}, involving moderate deviations from unity when alpha in (0,1) and c in R are constant parameters. The limit theory combines a functional law to a diffusion on D[0,infinity) and a central limit theorem. For c > 0, the limit theory of the first order serial correlation coefficient is Cauchy and is invariant to both the distribution and the dependence structure of the innovations. To our knowledge, this is the first invariance principle of its kind for explosive processes. The …
Temporal Aggregation And Risk-Return Relation, Jin Xing, Leping Wang, Jun Yu
Temporal Aggregation And Risk-Return Relation, Jin Xing, Leping Wang, Jun Yu
Research Collection School Of Economics
The function form of a linear intertemporal relation between risk and return is suggested by Merton's [1973. Econometrica 41, 867–887] analytical work for instantaneous returns, whereas empirical studies have examined the nature of this relation using temporally aggregated data, i.e., daily, monthly, quarterly, or even yearly returns. Our paper carefully examines the temporal aggregation effect on the validity of the linear specification of the risk–return relation at discrete horizons, and on its implications on the reliability of the resulting inference about the risk–return relation based on different observation intervals. Surprisingly, we show that, based on the standard Heston's [1993. Review …
Temporal Aggregation And Risk-Return Relation, Xing Jin, Leping Wang, Jun Yu
Temporal Aggregation And Risk-Return Relation, Xing Jin, Leping Wang, Jun Yu
Research Collection School Of Economics
The function form of a linear intertemporal relation between risk and return is suggested by Merton's [1973. Econometrica 41, 867–887] analytical work for instantaneous returns, whereas empirical studies have examined the nature of this relation using temporally aggregated data, i.e., daily, monthly, quarterly, or even yearly returns. Our paper carefully examines the temporal aggregation effect on the validity of the linear specification of the risk–return relation at discrete horizons, and on its implications on the reliability of the resulting inference about the risk–return relation based on different observation intervals. Surprisingly, we show that, based on the standard Heston's [1993. Review …
Modeling Transaction Data Of Trade Direction And Estimation Of Probability Of Informed Trading, Anthony S. Tay, Christopher Ting, Yiu Kuen Tse, Mitch Warachka
Modeling Transaction Data Of Trade Direction And Estimation Of Probability Of Informed Trading, Anthony S. Tay, Christopher Ting, Yiu Kuen Tse, Mitch Warachka
Research Collection School Of Economics
This paper implements the Asymmetric AutoregressiveConditional Duration (AACD) model of Bauwens and Giot (2003) to analyzeirregularly spaced transaction data of trade direction, namely buy versus sellorders. We examine the influence of lagged transaction duration, lagged volumeand lagged trade direction on transaction duration and direction. Our resultsare applied to estimate the probability of informed trading (PIN) based on theEasley, Hvidkjaer and O’Hara (2002) framework. Unlike the Easley-Hvidkjaer-O’Hara model, which uses the daily aggregate number of buy and sellorders, the AACD model makes full use of transaction data and allows forinteractions between buy and sell orders.
Statistics With Estimated Parameters, Zhenlin Yang, Yiu Kuen Tse, Zhidong Bai
Statistics With Estimated Parameters, Zhenlin Yang, Yiu Kuen Tse, Zhidong Bai
Research Collection School Of Economics
This paper studies a general problem of making inferences for functions of two sets of parameters where, when the first set is given, there exists a statistic with a known distribution. We study the distribution of this statistic when the first set of parameters is unknown and is replaced by an estimator. We show that under mild conditions the variance of the statistic is inflated when the unconstrained maximum likelihood estimator (MLE) is used, but deflated when the constrained MLE is used. The results are shown to be useful in hypothesis testing and confidence-interval construction in providing simpler and improved …
A Two-Stage Realized Volatility Approach To Estimation Of Diffusion Processes With Discrete Data, Peter C. B. Phillips, Jun Yu
A Two-Stage Realized Volatility Approach To Estimation Of Diffusion Processes With Discrete Data, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
This paper motivates and introduces a two-stage method of estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as developed in [Jacod, J., 1994] and [Barndorff-Nielsen, O., Shephard, N., 2002], to provide a regression model for estimating the parameters in the diffusion function. In the second stage, the in-fill likelihood function is derived by means of the Girsanov theorem and then used to estimate the parameters in the drift function. Consistency and asymptotic distribution theory for these estimates are established in various contexts. The finite …
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
It is well-known that maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size (T) and large cross section sample size (N) asymptotics. The estimation bias is particularly relevant in practical applications when T is small and the autoregressive parameter is close to unity. The present paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference (Gouriéroux et al., 1993), shows unbiasedness and analyzes efficiency. The method is implemented in a simple linear dynamic panel model, but has wider …
Household Heterogeneity And Optimal Inter-Temporal Pricing For A Durable-Good Monopoly, Winston T. H. Koh
Household Heterogeneity And Optimal Inter-Temporal Pricing For A Durable-Good Monopoly, Winston T. H. Koh
Research Collection School Of Economics
In this paper, I extend the analysis in Koh (2006) to examine the optimality of inter-temporal price discrimination for a durable-good monopoly in a model where infinitely-lived households consume both durable goods and a stream of non-durable goods subject to different inter-temporal budget constraints. I also consider the multi-dimensional setting where households differ in both inter-temporal budget constraints and the utilities they derive from the consumption of the durable good.
Mixing Frequencies: Stock Returns As A Predictor Of Real Output Growth, Anthony S. Tay
Mixing Frequencies: Stock Returns As A Predictor Of Real Output Growth, Anthony S. Tay
Research Collection School Of Economics
We investigate two methods for using daily stock returns to forecast, and update forecasts of, quarterly real output growth. Both methods aggregate daily returns in some manner to form a single stock market variable. We consider (i) augmenting the quarterly AR(1) model for real output growth with daily returns using a nonparametric Mixed Data Sampling (MIDAS) setting, and (ii) augmenting the quarterly AR(1) model with the most recent r -day returns as an additional predictor. We find that our mixed frequency models perform well in forecasting real output growth.
Simulation-Based Estimation Of Contingent-Claims Prices, Peter C. B. Phillips, Jun Yu
Simulation-Based Estimation Of Contingent-Claims Prices, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
A new methodology is proposed to estimate theortical prices of financial contingent-claims whose values are dependent on some other underlying financial assets. In the literature the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but is not necessarily the best method in finite samples. The present paper proposes instead a simulation-based method that improves the finite sample performance of the ML estimator while maintaining its good asymptotic properties. The methods are implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond pricing model, but have wider applicability. Monte Carlo …
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 …
Multivariate Stochastic Volatility, Manabu Asai, Michael Mcaleer, Jun Yu
Multivariate Stochastic Volatility, Manabu Asai, Michael Mcaleer, Jun Yu
Research Collection School Of Economics
The literature on multivariate stochastic volatility (MSV) models has developed significantly over the last few years. This paper reviews the substantial literature on specification, estimation and evaluation of MSV models. A wide range of MSV models is presented according to various categories, namely (i) asymmetric models; (ii) factor models; (iii) time-varying correlation models; and (iv) alternative MSV specifications, including models based on the matrix exponential transformation, Cholesky decomposition, Wishart autoregressive process, and the empirical range. Alternative methods of estimation, including quasi-maximum likelihood, simulated maximum likelihood, Monte Carlo likelihood, and Markov chain Monte Carlo methods, are discussed and compared. Various methods …
Lottery Rather Than Waiting-Line Auction, Winston T. H. Koh, Zhenlin Yang, Lijing Zhu
Lottery Rather Than Waiting-Line Auction, Winston T. H. Koh, Zhenlin Yang, Lijing Zhu
Research Collection School Of Economics
This paper investigates the allocative efficiency of two non-price allocation mechanisms – the lottery (random allocation) and the waiting-line auction (queue system) – for the cases where consumers possess identical time costs (the homogeneous case), and where time costs are correlated with time valuations (the heterogeneous case). We show that the relative efficiency of the two mechanisms depends critically on a scarcity factor (measured by the ratio of the number of objects available for allocation over the number of participants) and on the shape of the distribution of valuations. We show that the lottery dominates the waiting-line auction for a …
On Joint Modelling And Testing For Local And Global Spatial Externalities, Zhenlin Yang
On Joint Modelling And Testing For Local And Global Spatial Externalities, Zhenlin Yang
Research Collection School Of Economics
This paper concerns the joint modeling, estimation and testing for local and global spatial externalities. Spatial externalities have become in recent years a standard notion of economic research activities in relation to social interactions, spatial spillovers and dependence, etc., and have received an increasing attention by econometricians and applied researchers. While conceptually the principle underlying the spatial dependence is straightforward, the precise way in which this dependence should be included in a regression model is complex. Following the taxonomy of Anselin (2003, International Regional Science Review 26, 153-166), a general model is proposed, which takes into account jointly local and …
Set Inference For Semiparametric Discrete Games, Kyoo-Il Kim
Set Inference For Semiparametric Discrete Games, Kyoo-Il Kim
Research Collection School Of Economics
We consider estimation and inference of parameters in discrete games allowing for multiple equilibria, without using an equilibrium selection rule. We do a set inference while a game model can contain infinite dimensional parameters. Examples can include signaling games with discrete types where the type distribution is nonparametrically specified and entry-exit games with partially linear payoffs functions. A consistent set estimator and a confidence interval of a function of parameters are provided in this paper. We note that achieving a consistent point estimation often requires an information reduction. Due to this less use of information, we may end up a …