We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure...

Commonly used methods of production function estimation assume that a firm’s output quantity can be observed as data, but typical datasets contain only revenue, not output quantity. We examine the nonparametric identification of production function from revenue data when a firm faces a general...

I estimate CES aggregate production functions for the US, the UK, Japan, Germany, and Spain using data from the EU KLEMS database. I distinguish between three types of capital: information and communication technologies (ICT), intellectual property (IP) capital, and traditional capital. I assume...

We study the question whether a holder of standard essential patents (SEPs) should be allowed to choose the level in the value chain at which to offer a FRAND license to its SEPs. We give a pos-itive answer to this question for two reasons. First, the SEP holder and the social planner tend to...

This paper develops a dynamic programming method when the one-stage deviation principle in the sense of mechanism design literature doesn’t hold. The commonly used dynamic programming method is valid only if the one-stage deviation principle in the sense of mechanism design literature is...

Using neural networks, the present study replicates previous results on the prediction of student dropout obtained with decision trees and logistic regressions. For this purpose, multilayer perceptrons are trained on the same data as in the initial study. It is shown that neural networks lead to...

This paper defines isomorphism for network formation that is not mathematically isomorphic. Once the pattern of network formation is characterized, one can test for (i) location fixed effects, (ii) heterogeneity, (iii) private information allowing for long-term contracts. The paper provides...

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization. Quantum annealers attempt to solve an NP-hard problem by starting in a quantum superposition of all...

This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and interactive effects. The paper adopts the Common Correlated Effects (CCE) approach proposed by Pesaran (2006) and Chudik and Pesaran (2015) and demonstrates that the extension...

This paper considers the problem of identification, estimation and inference in the case of spatial panel data models with heterogeneous spatial lag coefficients, with and without (weakly) exogenous regressors, and subject to heteroskedastic errors. A quasi maximum likelihood (QML) estimation...