The paper provides historical and analytical perspectives for the assessment of the challenges and opportunities of cattle raising activities in the transition toward a low-carbon agriculture in Brazil. It is organized as follows. The first section poses the problem. The second presents long run...

The paper provides historical and analytical perspectives for the assessment of the challenges and opportunities of cattle raising activities in the transition towards a lowcarbon agriculture in Brazil. It is organized as follows. The next section presents long run historical perspectives on the...

This paper provides estimates of the capitalization of the Single Payment Scheme (SPS) payment of the Common Agricultural Policy (CAP) on agricultural land rental rates. We address problems of unobserved heterogeneity and sample selection. As the 2013 CAP Reform calls for the harmonization of...

Irrigation and land use are crucial issues in rural sustainable development. The current study modifies the sustainable framework of livelihoods to clarify the role of irrigation management in farmers' land-use choices. A five-wave panel dataset of 1,534 farms for the period 2008-2016 in Viet...

This paper develops the minimal asymptotic distributions for estimators of panel data models with incidental parameters

This paper shows how the dynamic linear model with fixed regressors can be efficiently estimated. This dynamic model can be used to distinguish spurious correlation from state dependence and we show that the integrated likelihood estimator is adaptive for any asymptotics with T increasing where...

GMM estimation of autoregressive panel data equations in error-ridden variables when the noise has memory, is considered. The impact of variation in the memory length in signal and noise spread and in the degree of individual heterogeneity are discussed with respect to finite sample bias, using...

An autoregressive fixed effects panel data equation in error-ridden endogenous and exogenous variables, with finite memory of disturbances, latent regressors and measurement errors is considered. Finite sample properties of GMM estimators are explored by Monte Carlo (MC) simulations. Two kinds...

The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random measurement errors in an autoregressive panel data model. Finite memory of disturbances, latent regressors and measurement errors is assumed. Two specializations of GMM are...