Exact inference methods for first-order autoregressive distributed lag models

Article Abstract:

Exact inference techniques were developed to effectively deal with first-order autoregressive distributed lag models. Formulation of the techniques was achieved after the generalized bounds test procedures were combined with methods used in removing test statistics' nuisance parameters. Through such combination, generation of exact inference techniques was achieved on almost any type of hypothesis on the coefficients of a first-order autoregressive distributed lag model.

Monte Carlo method, Monte Carlo methods, Autoregression (Statistics)

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Semiparametric latent variable model estimation with endogenous or mismeasured regressors

Article Abstract:

Semiparametric identification process was undertaken in relation to a general latent variable model coefficients with endogenous or mismeasured regressors. Semiparametric identification was derived through utilization of instruments that are unrelated with errors and a powerful exclusion restriction. Through semiparametric identification, simple root estimators were developed.

Latent variables

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On the robustness of cointegration methods when regressors almost have unit roots

Article Abstract:

The robustness of cointegration techniques was assessed when regressors nearly have unit roots. It was established that the validity of inferences related to cointegrating vector depends heavily on the robustness of cointegration methods. The consistency of cointegrating vectors' whilst point estimates was proven through the use of local to unity asymptotic approximations.

Statistics, Information theory, Statistics (Mathematics), Robust statistics, Robustness (Statistics), Information theory in economics

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