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Estimating quadratic variation using realized variance (replication data)
This paper looks at some recent work on estimating quadratic variation using realized variance (RV)?that is, sums of M squared returns. This econometrics has been motivated by... -
Estimating shocks and impulse response functions (replication data)
This paper examines the issue of how to identify the shocks in a cointegrated VAR when the following assumptions are made: the variables can be classified as endogenous or... -
Serially correlated variables in dynamic, discrete choice models (replication...
This paper discusses the problems that are encountered when dynamic, discrete choice models are specified with continuous, serially correlated state variables. A variety of... -
Investigating stability and linearity of a German M1 money demand function (r...
Starting from a linear error correction model (ECM) the stability and linearity of a German M1 money demand function are investigated, applying smooth transition regression... -
Estimation in large and disaggregated demand systems: an estimator for condit...
Empirical demand systems that do not impose unreasonable restrictions on preferences are typically non-linear. We show, however, that all popular systems possess the property of... -
Jackknife instrumental variables estimation (replication data)
Two-stage-least-squares (2SLS) estimates are biased towards the probability limit of OLS estimates. This bias grows with the degree of over-identification and can generate... -
A general dependence test and applications (replication data)
We describe a test, based on the correlation integral, for the independence of a variable and a vector that can be used with serially dependent data. Monte Carlo simulations... -
An empirical application of stochastic volatility models (replication data)
This paper studies the empirical performance of stochastic volatility models for twenty years of weekly exchange rate data for four major currencies. We concentrate on the... -
Testing non-nested semiparametric models: an application to Engel curves spec...
This paper proposes a test statistic for discriminating between two partly non-linear regression models whose parametric components are non-nested. The statistic has the form of... -
HETEROGENEITY, EXCESS ZEROS, AND THE STRUCTURE OF COUNT DATA MODELS (replicat...
This paper demonstrates that the unobserved heterogeneity commonly assumed to be the source of overdispersion in count data models has predictable implications for the... -
SEMI-PARAMETRIC ESTIMATION OF HURDLE REGRESSION MODELS WITH AN APPLICATION TO...
This paper develops a semi-parametric estimation method for hurdle (two-part) count regression models. The approach in each stage is based on Laguerre series expansion for the... -
COUNT DATA REGRESSION USING SERIES EXPANSIONS: WITH APPLICATIONS (replication...
A new class of parametric regression models for both under? and overdispersed count data is proposed. These models are based on squared polynomial expansions around a Poisson... -
Numerical distribution functions for unit root and cointegration tests (repli...
This paper employs response surface regressions based on simulation experiments to calculate distribution functions for some well-known unit root and cointegration test... -
Persistence of shocks on seasonal processes (replication data)
The paper addresses the issue of measuring the persistence of shocks on seasonally integrated processes observed at quarterly intervals. We show that the amplitude of the... -
On a double-threshold autoregressive heteroscedastic time series model (repli...
Tong's threshold models have been found useful in modelling nonlinearities in the conditional mean of a time series. The threshold model is extended to the so-called... -
Money demand revisited: An operational subjective approach (replication data)
This paper proposes a method of data analysis founded on the philosophy and understanding of uncertain knowledge developed by Bruno de Finetti. Specifically, the paper... -
Analysing inflation by the fractionally integrated ARFIMA-GARCH model (replic...
This paper considers the application of long-memory processes to describing inflation for ten countries. We implement a new procedure to obtain approximate maximum likelihood... -
A class of binary response models for grouped duration data (replication data)
This paper explores the relationship between conventional models for binary response such as the probit and logit, and the proportional hazard (PH) and related specifications... -
Forecasting exchange rates using feedforward and recurrent neural networks (r...
In this paper we investigate the out-of-sample forecasting ability of feedforward and recurrent neural networks based on empirical foreign exchange rate data. A two-step... -
Maximum likelihood estimation of a GARCH-stable model (replication data)
Maximum likelihood is used to estimate a generalized autoregressive conditional heteroskedastic (GARCH) process where the residuals have a conditional stable distribution...
