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A distribution-free least squares estimator for censored linear regression models
Non-parametric maximum likelihood estimation of censored regression models
Choice-based samples
Operational characteristics of maximum score estimation
Modified lagrange multiplier tests for problems with one-sided alternatives
Gradual switching multivariate regression models with stochastic cross-equational constraints and an application to the Klem translog production model
A simple, flexible distributed lag technique
Generalized autoregressive conditional heteroskedasticity
广义自回归条件异方差
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class of parametric models are derived. Maximum likelihood estimation and testing are also considered. Finally an empirical example relating to the uncertainty of the inflation rate is presented.
Estimated parameters as independent variables
The frequency of price adjustment
价格调整的频率
Data on the newsstand prices of American magazines is used to investigate the determinants of the frequency of nominal price change. Magazine price changes, often coming after real prices have fallen by one quarter, provide strong evidence for monopolistic sticky price models. The data is examined by applying a fixed effects logit specification to the price change rule implied by a target-threshold model of a firm facing general price inflation, an uncertain future and…
A Monte Carlo evaluation of the power of some tests for heteroscedasticity
Identification of linear stochastic models with covariance restrictions
Logit versus discriminant analysis
A note on price adjustment models in disequilibrium econometrics
Specification testing when score test statistics are identically zero
Errors in variables in panel data
面板数据中的变量测量误差
Panel data based on various longitudinal surveys have become ubiquitous in economics in recent years. Estimation using the analysis of covariance approach allows for control of various "individual effects" by estimation of the relevant relationships from the "within" dimension of the data. Quite often, however, the "within" results are unsatisfactory, "too low" and insignificant. Errors of measurement in the independent variables whose relative importance gets magnified in…