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	Provedor de dados AgEcon (12) Autor Newson, Roger (2) Nichols, Austin (2) Becker, Sascha O. (1) Deuss, Annelies (1) Dunn, Graham (1) Emsley, Richard (1) Hahn, Jinyong (1) Hirano, Keisuke (1) Ichino, Andrea (1) Karlan, Dean S. (1) Liu, Xiangping (1) Lunt, Mark (1) Lynch, Lori (1) Mullally, Conner (1) Nannicini, Tommaso (1) Pickles, Andrew (1) Schoengold, Karina (1) Sunding, David L. (1) Mais... Palavra-chave Propensity score (12) Research Methods/ Statistical Methods (9) Matching (5) C14 (2) Causal inference (2) Discontinuity (2) Excluded instrument (2) Instrumental variables (2) International Development (2) Ivreg (2) Ivreg2 (2) Ivregress (2) Local polynomial (2) Lpoly (2) Match (2) Nnmatch (2) Panel (2) Psmatch2 (2) Ranktest (2) Rd (2) Mais... Tipo do documento Article (5) Conference Paper or Presentation (4) Journal Article (2) Working or Discussion Paper (1) Ano 2011 (3) 2009 (1) 2008 (2) 2007 (3) 2006 (2) 2002 (1) Mais... País United States (12) Idioma Inglês (12)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 12 Primeira ... 1 ... Última Adaptive Experimental Design Using the Propensity Score AgEcon Hahn, Jinyong; Hirano, Keisuke; Karlan, Dean S.. Many social experiments are run in multiple waves, or are replications of earlier social experiments. In principle, the sampling design can be modified in later stages or replications to allow for more efficient estimation of causal effects. We consider the design of a two-stage experiment for estimating an average treatment effect, when covariate information is available for experimental subjects. We use data from the first stage to choose a conditional treatment assignment rule for units in the second stage of the experiment. This amounts to choosing the propensity score, the conditional probability of treatment given covariates. We propose to select the propensity score to minimize the asymptotic variance bound for estimating the average treatment... Tipo: Working or Discussion Paper Palavras-chave: Experimental design; Propensity score; Efficiency bound; Research Methods/ Statistical Methods; C1; C14; C9; C93; C13. Ano: 2009 URL: http://purl.umn.edu/47107 Causal inference with observational data AgEcon Nichols, Austin. Problems with inferring causal relationships from nonexperimental data are briefly reviewed, and four broad classes of methods designed to allow estimation of and inference about causal parameters are described: panel regression, matching or reweighting, instrumental variables, and regression discontinuity. Practical examples are offered, and discussion focuses on checking required assumptions to the extent possible. Tipo: Article Palavras-chave: Xtreg; Psmatch2; Nnmatch; Ivreg; Ivreg2; Ivregress; Rd; Lpoly; Xtoverid; Ranktest; Causal inference; Match; Matching; Reweighting; Propensity score; Panel; Instrumental variables; Excluded instrument; Weak identification; Regression; Discontinuity; Local polynomial; Research Methods/ Statistical Methods. Ano: 2007 URL: http://purl.umn.edu/119292 Confidence intervals for rank statistics: Percentile slopes, differences, and ratios AgEcon Newson, Roger. I present a program, censlope, for calculating confidence intervals for generalized Theil–Sen median (and other percentile) slopes (and per-unit ratios) of Y with respect to X. The confidence intervals are robust to the possibility that the conditional population distributions of Y , given different values of X, differ in ways other than location, such as having unequal variances. censlope uses the program somersd and is part of the somersd package. censlope can therefore estimate confounder-adjusted percentile slopes, limited to comparisons within strata defined by values of confounders, or by values of a propensity score representing multiple confounders. Iterative numerical methods have been implemented in the Mata language, enabling efficient... Tipo: Article Palavras-chave: Somersd; Censlope; ALSPAC; Robust; Confidence interval; Rank; Nonparametric; Median; Percentile; Slope; Difference; Ratio; Kendall's τ; Somers' D; Theil–Sen; Hodges–Lehmann; Confounder adjusted; Propensity score; Research Methods/ Statistical Methods. Ano: 2006 URL: http://purl.umn.edu/119241 Confidence intervals for rank statistics: Somers' D and extensions AgEcon Newson, Roger. Somers’ D is an asymmetric measure of association between two variables, which plays a central role as a parameter behind rank or nonparametric statistical methods. Given predictor variable X and outcome variable Y , we may estimate DYX as a measure of the effect of X on Y , or we may estimate DXY as a performance indicator of X as a predictor of Y. The somersd package allows the estimation of Somers’ D and Kendall’s τα with confidence limits as well as p-values. The Stata 9 version of somersd can estimate extended versions of Somers’ D not previously available, including the Gini index, the parameter tested by the sign test, and extensions to left- or right-censored data. It can also estimate stratified versions of Somers’ D, restricted to pairs in the... Tipo: Journal Article Palavras-chave: Somersd; Somers' D; Kendall's τ_a; Harrell's c; ROC area; Gini index; Population-attributable risk; Rank correlation; Rank-sum test; Wilcoxon test; Sign test; Confidence intervals; Nonparametric methods; Propensity score; Research Methods/ Statistical Methods. Ano: 2006 URL: http://purl.umn.edu/117583 Development in the Midst of Drought: Evaluating an Agricultural Extension and Credit Program in Nicaragua. AgEcon Mullally, Conner. Abstract: This essay is an evaluation of year one of the Rural Business Development (RBD) program for small rice farmers in León, Nicaragua. The RBD program is administered by the Millennium Challenge Corporation, and is designed to deliver agricultural extension advice and affordable credit in the form of inputs to farm households. This essay estimates the average impact of the program on rice yields and revenues utilizing inverse propensity score weighting combined with linear regression. In conducting statistical inference, it also accounts for the fact that agricultural outcomes are likely correlated over space in a small area such as the one studied here. The results suggest that the program had no impact on average, likely due to the presence of a... Tipo: Conference Paper or Presentation Palavras-chave: Development; Agriculture; Extension; Credit; Spatial; Propensity score; International Development. Ano: 2011 URL: http://purl.umn.edu/108498 Do Agricultural Preservation Programs Affect Farmland Conversion? AgEcon Liu, Xiangping; Lynch, Lori. More than 124 governmental entities concerned about suburban sprawl and farmland loss have implemented farmland preservation programs preserving 1.67 million acres at a cost of $3.723 billion. We ask how effective are these programs in slowing the rate of farmland loss. Using a unique 50-year 269 county panel data set on preservation programs and farmland loss for six Mid-Atlantic States, we employ the propensity score matching method to find strong empirical evidence that these programs have had a statistically significant effect on the rate of farmland loss. Preservation programs on average decrease the rate of farmland loss by 2.4 percentage points; a 33% decrease from the average 5-year rate of 7.31%. Tipo: Conference Paper or Presentation Palavras-chave: Agricultural preservation programs; Farmland; Propensity score; Farmland conversion; Urban-rural interface; Land Economics/Use. Ano: 2007 URL: http://purl.umn.edu/9764 Erratum and discussion of propensity–score reweighting AgEcon Nichols, Austin. Tipo: Article Palavras-chave: Xtreg; Psmatch2; Nnmatch; Ivreg; Ivreg2; Ivregress; Rd; Lpoly; Xtoverid; Ranktest; Causal inference; Match; Matching; Reweighting; Propensity score; Panel; Instrumental variables; Excluded instrument; Weak identification; Regression; Discontinuity; Local polynomial; Research Methods/ Statistical Methods. Ano: 2008 URL: http://purl.umn.edu/122619 Estimation of average treatment effects based on propensity scores AgEcon Becker, Sascha O.; Ichino, Andrea. In this paper, we give a short overview of some propensity score matching estimators suggested in the evaluation literature, and we provide a set of Stata programs, which we illustrate using the National Supported Work (NSW) demonstration widely known in labor economics. Tipo: Journal Article Palavras-chave: Propensity score; Matching; Average treatment effect; Evaluation; Research Methods/ Statistical Methods. Ano: 2002 URL: http://purl.umn.edu/116022 Implementing double-robust estimators of causal effects AgEcon Emsley, Richard; Lunt, Mark; Pickles, Andrew; Dunn, Graham. This article describes the implementation of a double-robust estimator for pretest–posttest studies (Lunceford and Davidian, 2004, Statistics in Medicine 23: 2937–2960) and presents a new Stata command (dr) that carries out the procedure. A double-robust estimator gives the analyst two opportunities for obtaining unbiased inference when adjusting for selection effects such as confounding by allowing for different forms of model misspecification; a double-robust estimator also can offer increased efficiency when all the models are correctly specified. We demonstrate the results with a Monte Carlo simulation study, and we show how to implement the double-robust estimator on a single simulated dataset, both manually and by using the dr command. Tipo: Article Palavras-chave: Dr; Double-robust estimators; Causal models; Confounding; Inverse probability of treatment weights; Propensity score; Research Methods/ Statistical Methods. Ano: 2008 URL: http://purl.umn.edu/122597 Input Price Risk and the Adoption of Conservation Technology AgEcon Schoengold, Karina; Sunding, David L.. Replaced with revised version of poster 07/12/11. Tipo: Conference Paper or Presentation Palavras-chave: Price risk; Technology adoption; Matching; Propensity score; Environmental Economics and Policy; Resource /Energy Economics and Policy; Risk and Uncertainty; Q1; Q5. Ano: 2011 URL: http://purl.umn.edu/103857 Simulation-based sensitivity analysis for matching estimators AgEcon Nannicini, Tommaso. This article presents a Stata program (sensatt) that implements the sensitivity analysis for matching estimators proposed by Ichino, Mealli, and Nannicini (Journal of Applied Econometrics, forthcoming). The analysis simulates a potential confounder to assess the robustness of the estimated treatment effects with respect to deviations from the conditional independence assumption. The program uses the commands for propensity-score matching (att* ) developed by Becker and Ichino (Stata Journal 2: 358–377). I give an example by using the National Supported Work demonstration, widely known in the program evaluation literature. Tipo: Article Palavras-chave: Sensatt; Sensitivity analysis; Matching; Propensity score; Program evaluation; Research Methods/ Statistical Methods. Ano: 2007 URL: http://purl.umn.edu/119280 The Economic Growth Impacts of Sugarcane Expansion In Brazil: An Inter-Regional Analysis AgEcon Deuss, Annelies. Tipo: Conference Paper or Presentation Palavras-chave: Brazil; Sugarcane expansion; Economic growth; Propensity score; Ethanol; Agricultural and Food Policy; Crop Production/Industries; International Development; Research Methods/ Statistical Methods; C14; C21; O13; R13. Ano: 2011 URL: http://purl.umn.edu/103564 Registros recuperados: 12 Primeira ... 1 ... Última

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