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in an application related to the recent housing crisis and the Great Recession (Dec 2007 - Jun 2009). Specifically, we analyze how various socioeconomic & demographic factors and exposure to financial distress are associated with differences in views on the financial bene- fits of homeownership following the Great Recession. The results increase our understanding and offer new insights which may be important for policymakers and US housing market. 

The remainder of the paper is organized as follows. Section 2 presents some fundamen- tal properties of the GAL distribution. Section 3 presents the FBQROR model and its estimation procedure. Section 4 illustrates the algorithm in two simulation studies and Sec- tion 5 implements the algorithm to examine US public opinion on homeownership. Section 6 presents some concluding remarks. 

## 2. The GAL Distribution 

The GAL distribution is obtained by introducing a shape parameter into the mean of the normal kernel in the normal-exponential mixture representation of the AL distribution and mixing with respect to a half-normal distribution (Yan and Kottas, 2017). This hierarchical representation allows the skewness and mode to vary for a given quantile/percentile and hence imports the much needed flexibility required for Bayesian quantile regression. 

Suppose Y is a random variable that has the following mixture representation, 

<img src='content_image/304282.jpg'>

where W ∼ E (1), S ∼ N $^{+}$(0 , 1), U ∼ N (0 , 1), A ≡ A ( p ) = 1 − 2 p p (1 − p ) and B ≡ B ( p ) = 2 p (1 − p $_{)}$. Here, E , N + and N denote exponential, half-normal and normal distributions, respectively. Then, Y follows a GAL distribution denoted Y ∼ GAL ( µ, σ, p, α ) and has the pdf , 

<img src='content_image/304283.jpg'>

