We estimate an equilibrium model of decision-making in the US Supreme Court which takes into account both private information and ideological differences between justices. We measure the value of information in the court by the probability that a justice votes differently from how she would have voted without case-specific information. Our results suggest a sizable value of information: in 44% ...

This paper examines asymptotic expansions for estimation errors expressed explicitly as functions of underlying random variables. Taylor series expansions are obtained from which "rst and second moment approximations are derived. While the expansions are essentially equivalent to the traditional Nagar type, the terms are expressed in a form which enables moment approximations to be obtained in ...

We complement existing inferential theory for panel factor models by deriving the asymptotics for the …rst di¤erences of the estimated factors and common components obtained from a non-stationary panel factor model. As an application, we propose an estimator for the long run variance of the common components. JEL Classi…cation: C13, C23. Keywords: Non-stationary panels, common factors, common c...

Significant nonlinearities are found in several cyclical components macroeconomic time series across countries. Standard equilibrium models of business cycles successfully explain most first and second moments of these time series. However, this paper shows that a model of this class cannot replicate nonlinear features of the data. Applying the Efficient Method of Moments methodology to build a...

In parametric stochastic frontier models, the composed error is specified as the sum of a two-sided noise component and a one-sided inefficiency component, which is usually assumed to be half-normal, implying that the error distribution is skewed in one direction. In practice, however, estimation residuals may display skewness in the wrong direction. Model respecification or pulling a new sampl...

In this note, we propose a least squares method with l1 penalty (based on the “Lasso”) to estimate models with latent variables. Our approach addresses the high dimensionality of these models, due to the presence of unknown distribution functions. It builds on a recent proposal by Bunea, Tsybakov, Wegkamp and Barbu (2010, Annals of Statistics) that uses penalized least squares for density estim...

considering the importance of government fiscal policy (government spending and state tax income) in economy and its effectiveness in well-being of people, this paper examines the effects of fiscal policy on poverty during the period 1386-1363 in iran. in this paper, considering the fact that poverty changes can be divided to changes in economic growth and changes in income distribution; initia...

We analyze a time series of global temperature anomaly distributions to identify and estimate persistent features in climate change. In our study, temperature densities, obtained from globally distributed data over the period from 1850 to 2012, are regarded as a time series of functional observations that are changing over time. We employ a formal test for the existence of functional unit roots...

Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models. We study this link using two notions of temporal dependence: β − mixing and ρ − mixing. We show that β − mixing and ρ − mixing with exponential decay are essentially equivalent concepts for scalar diffusions. For stationary diffusions that fail to be ρ−mixing, we show that they are s...