Food, energy, and water (FEW) systems play a fundamental role in determining societal health and economic well-being. However, current and expected changes in climate, population, and land use place these systems under considerable stress. To improve policies that target these challenges, this review highlights the need for integrating biophysical and economic models of the FEW nexus. We discuss advancements in modeling individual components that comprise this system and outline fundamental research needs for these individual areas as well as for model integration. Though great strides have been made in individual and integrated modeling, we nevertheless find a considerable need for improved integration of economic decision-making with biophysical models. We also highlight a need for improved model validation.
This paper develops a novel bootstrap procedure to obtain robust bias-corrected confidence intervals in regression discontinuity (RD) designs using the uniform kernel. The procedure uses a residual bootstrap from a second order local polynomial to estimate the bias of the local linear RD estimator; the bias is then subtracted from the original estimator. The bias-corrected estimator is then bootstrapped itself to generate valid confidence intervals. The confidence intervals generated by this procedure are valid under conditions similar to Calonico, Cattaneo and Titiunik's (2014, Econometrica) analytical correction-i.e. when the bias of the naive regression discontinuity estimator would otherwise prevent valid inference. This paper also provides simulation evidence that our method is as accurate as the analytical corrections and we demonstrate its use through a reanalysis of Ludwig and Miller's (2008) Head Start dataset.
This paper weakens the size and moment conditions needed for typical block bootstrap methods (i.e., the moving blocks, circular blocks, and stationary bootstraps) to be valid for the sample mean of Near-Epoch-Dependent (NED) functions of mixing processes; they are consistent under the weakest conditions that ensure the original NED process obeys a central limit theorem (CLT), established by De Jong (1997, Econometric Theory 13(3), 353–367). In doing so, this paper extends De Jong’s method of proof, a blocking argument, to hold with random and unequal block lengths. This paper also proves that bootstrapped partial sums satisfy a functional CLT (FCLT) under the same conditions.
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