We reexamine the empirical relevance of habit formation preferences with micro-data on households' portfolio choices. We first derive the analytical solution to the risky asset share in a theoretical model with both habits and time-varying labor income. Our analytical results indicate that (1)...

In this article, we explore whether relative risk aversion varies with wealth. First, we derive theoretical predictions on how risky shares respond to wealth uctuations in a portfolio choice model with both external habits and time-varying labor income. Our analytical results indicate that: (1)...

Varying-coefficient linear models arise from multivariate nonparametric regression, nonlinear time series modelling and forecasting, functional data analysis, longitudinal data analysis, and others. It has been a common practice to assume that the vary-coefficients are functions of a given...

We deal with smoothed estimators for conditional probability functions of discrete-valued time series {Yt} under two different settings. When the conditional distribution of Yt given its lagged values falls in a parametric family and depends on exogenous random variables, a smoothed maximum...

The local linear regression technique is applied to estimation of functional-coefficient regression models for time series data. The models include threshold autoregressive models and functional-coefficient autoregressive models as special cases but with the added advantages such as depicting...

A fundamental issue of applying a copula method in applications is how to choose an appropriate copula function for a given problem. In this article we address this issue by proposing a new copula selection approach via penalized likelihood plus a shrinkage operator. The proposed method selects...

Researchers have constantly asked whether stock returns can be predicted by some macroeconomic data. However, it is known that macroeconomic data may exhibit nonstationarity and/or heavy tails, which complicates existing testing procedures for predictability. In this paper we propose novel...

We show that independently repeated cross-sectional data can reduce the asymptotic bias when instruments are weakly correlated to the endogenous variables. When both N and T go to infinite, we can obtain consistent estimators even if instruments are weak.