In many empirical studies, researchers seek to estimate causal relationships using instrumental variables. When only one valid instrumental variable is available, researchers are limited to estimating linear models, even when the true model may be non-linear. In this case, ordinary least squares...

Neyman and Scott (1948) define the incidental parameter problem. In panel data with T observations per individual and unobservable individual- specific effects, the inconsistency of the maximum likelihood estimator of the common parameters is in general of the order 1/T. This paper considers the...

Structural vector autoregressions (SVARs) are widely used for policy analysis and to provide stylized facts for dynamic general equilibrium models. Yet there have been no workable rank conditions to ascertain whether an SVAR is globally identified. When identifying restrictions such as long-run...

We propose a new information criterion for impulse response function matching estimators (IRFMEs) of the structural parameters of dynamic stochastic general equilibrium (DSGE) macroeconomic models. An advantage of our procedure is that it allows researchers to select the impulse responses that...

A two-regime self-exciting threshold autoregressive process is estimated for quarterly aggregate GDP of the fifteen countries that compose the European Union, and the forecasts from this nonlinear model are compared, by means of a Monte Carlo simulation, with those from a simple autoregressive...

In this paper we consider conditions under which the estimation of a log-linearized Euler equation for consumption yields consistent estimates of preference parameters. When utility is isoelastic and a sample covering a long time period is available, consistent estimates are obtained from the...

P-splines are a popular approach for fitting nonlinear effects of continuous covariates in semiparametric regression models. Recently, a Bayesian version for P-splines has been developed on the basis of Markov chain Monte Carlo simulation techniques for inference. In this work we adopt and...

We develop econometric models of ascending (English) auctions which allow for both bidder asymmetries as well as common and/or private value components in bidders' underlying valuations We show that the equilibrium inverse bid functions in each round of the auction are implicitly defined...

We develop a new estimation methodology for dynamic optimization models with unobserved state variables Our approach is semiparametric in the sense of not requiring explicit parametric assumptions to be made concerning the distribution of these unobserved state variables We propose a two-step...

Focussing on the prime example of CO2 emissions, we discuss several important theoretical and econometric problems that arise when studying environmental Kuznets curves (EKCs). The dominant theoretical approach is given by integrated assessment modelling, which consists of economic models that...