Inference regarding multiple structural changes in linear models with endogenous regressors

This paper considers the linear model with endogenous regressors and multiple changes in the parameters at unknown times. It is shown that minimization of a Generalized Method of Moments criterion yields inconsistent estimators of the break fractions, but minimization of the Two Stage Least Squares (2SLS) criterion yields consistent estimators of these parameters. We develop a methodology for estimation and inference of the parameters of the model based on 2SLS. The analysis covers the cases where the reduced form is either stable or unstable. The methodology is illustrated via an application to the New Keynesian Phillips Curve for the US.     

A simulation study of an ASEAN monetary union

This paper analyzes some pros and cons of a monetary union for the ASEAN¹ countries, excluding Myanmar. We estimate a stylized open-economy dynamic general equilibrium model for the ASEAN countries. Using the framework of linear quadratic differential games, we contrast the potential gains or losses for these countries due to economic shocks, in case they maintain their status-quo, they coordinate their monetary and/or fiscal policies, or form a monetary union. Assuming for all players open-loop information, we conclude that there are substantial gains from cooperation of monetary authorities. We also find that whether a monetary union improves upon monetary cooperation depends on the type of shocks and the extent of fiscal policy cooperation. Results are based both on a theoretical study of the structure of the estimated model and a simulation study.     

Estimation and inference in unstable nonlinear least squares models

There is compelling evidence that many macroeconomic and financial variables are not generated by linear models. This evidence is based on testing linearity against either smooth nonlinearity or piece-wise linearity, but there is no framework that encompasses both. This paper provides an econometric framework that allows for both breaks and smooth nonlinearity in between breaks. We estimate the unknown break-dates simultaneously with other parameters via nonlinear least-squares. Using new central limit results for nonlinear processes, we provide inference methods on break-dates and parameter estimates and several instability tests. We illustrate our methods via simulated and empirical smooth transition models with breaks.     

Change point estimation in panel data with time-varying individual effects

Existing panel data methods remove unobserved individual effects before change point estimation through data transformations such as first-differencing. In this paper, we show that multiple change points can be consistently estimated in short panels via ordinary least squares. Since no data variation is removed before change point estimation, our method has better small-sample properties compared to first-differencing methods. We also propose two tests that identify whether the change points found by our method originate in the slope parameters or in the covariance of the regressors with individual effects. We illustrate our method via modeling the environmental Kuznets curve and the US house price expectations after the financial crisis.