Abstract:This chapter considers estimation and inference in case of stationary and non-stationary autoregressive processes as estimated by quantile regressions. It reports the autocorrelations of the residuals...This chapter considers estimation and inference in case of stationary and non-stationary autoregressive processes as estimated by quantile regressions. It reports the autocorrelations of the residuals of the estimated AR(1) model, computed at the conditional mean. Tests of stationarity are implemented together with other closely related tests, although the latter are not specifically defined for the quantile regression model. The presence of unit root, besides causing a nonstandard distribution of the t test, has an additional relevant implication in a regression model. The case of spurious regression and of cointegrated variables are discussed in simulated data sets and for the consumption function. The test for cointegration brings to the analysis of changing coefficient models and to the test functions defined to detect them. The quantile regression conditionally heteroskedastic model concludes the chapter by further analyzing the inflation rate series.Read More
Publication Year: 2018
Publication Date: 2018-08-20
Language: en
Type: other
Indexed In: ['crossref']
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