Title: Models with dependent and with non‐identically distributed data
Abstract:This chapter focuses on the quantile regression estimators for models characterized by heteroskedastic and by dependent errors. It considers the precision of the quantile regression model in the case ...This chapter focuses on the quantile regression estimators for models characterized by heteroskedastic and by dependent errors. It considers the precision of the quantile regression model in the case of independent and identically distributed (i.i.d.) errors, taking a closer look at the computation of confidence intervals and hypothesis testing on each estimated coefficient. The chapter extends the analysis to the case of non-identically distributed errors, discussing different ways to verify the presence of heteroskedasticity in the data. It takes into account the case of dependent observations and discusses the estimation of an exchange rate equation characterized by serially correlated errors.Read More
Publication Year: 2014
Publication Date: 2014-08-04
Language: en
Type: other
Indexed In: ['crossref']
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