1. Random-coefficient Models 1. Markov-switching model (MRS) 2. Threshold model 3. Quantile Regression model (QR)

2. Constant-coefficient regression Constant-coefficient regression models have been applied extensively in statistics Various random-coefficient models have also emerged as viable competitors in particular fields of application –Quantile regression –Threshold model –Markov switching model The conventional regression model –Cross-sectional data –Time-series data

3. Constant-coefficient regression

4. We assume the sensitivities (i.e. β) of y to the x variables are identical for all observations the beta is uniform from i=1…,N the beta is uniform from t=1…,T The beta= the first derivative of y with respect to x

5. Threshold Models The state is observable The state is identified by if a threshold variable exceed a critical value The keys – how to define the threshold variable? – how to estimate the threshold parameter? Applications –cross-sectional data –time-series data

6. Markov-switching Models The state is unobservable Estimate the probability of a specific state at each time point Transition probability system –How to decide the probability? Applications –Time-series data

7. Quantile regression (QR) model The effect of x on y could change by the quantile level of y What is the quantile? –the quantile is a statistical term describing a division of observations into certain defined intervals based upon the values of the data –The magnitude of the y variable in term of probability Applications –Cross-sectional data

8. How Many Years for One SSCI Publication?

12. How many SSCI journals in the world? Economics: 191 Management: 81 Finance: 45 Accounting: 20 (?)

13. How to find the reference papers?