Quantile Regression with Generated Regressors

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ISBN 13 :
Total Pages : 51 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Quantile Regression with Generated Regressors by : Liqiong Chen

Download or read book Quantile Regression with Generated Regressors written by Liqiong Chen and published by . This book was released on 2018 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step estimation procedure, where the generated regressors are computed in the first step. The asymptotic properties of the two-step estimator, namely, consistency and asymptotic normality are established. We show that the asymptotic variance-covariance matrix needs to be adjusted to account for the first-step estimation error. We propose a general estimator for the asymptotic variance-covariance, establish its consistency, and develop testing procedures for linear hypotheses in these models. Monte Carlo simulations to evaluate the finite-sample performance of the estimation and inference procedures are provided. Finally, we apply the proposed methods to study Engel curves for various commodities using data from the UK Family Expenditure Survey. We document strong heterogeneity in the estimated Engel curves along the conditional distribution of the budget share of each commodity. The empirical application also emphasizes that correctly estimating confidence intervals for the estimated Engel curves by the proposed estimator is of importance for inference.

Quantile Regression

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Publisher : John Wiley & Sons
ISBN 13 : 111886364X
Total Pages : 311 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Quantile Regression by : Marilena Furno

Download or read book Quantile Regression written by Marilena Furno and published by John Wiley & Sons. This book was released on 2018-07-18 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains an overview of several technical topics of Quantile Regression Volume two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores topics including robustness, expectiles, m-quantile, decomposition, time series, elemental sets and linear programming. Graphical representations are widely used to visually introduce several issues, and to illustrate each method. All the topics are treated theoretically and using real data examples. Designed as a practical resource, the book is thorough without getting too technical about the statistical background. The authors cover a wide range of QR models useful in several fields. The software commands in R and Stata are available in the appendixes and featured on the accompanying website. The text: Provides an overview of several technical topics such as robustness of quantile regressions, bootstrap and elemental sets, treatment effect estimators Compares quantile regression with alternative estimators like expectiles, M-estimators and M-quantiles Offers a general introduction to linear programming focusing on the simplex method as solving method for the quantile regression problem Considers time-series issues like non-stationarity, spurious regressions, cointegration, conditional heteroskedasticity via quantile regression Offers an analysis that is both theoretically and practical Presents real data examples and graphical representations to explain the technical issues Written for researchers and students in the fields of statistics, economics, econometrics, social and environmental science, this text offers guide to the theory and application of quantile regression models.

Quantile Regression

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Publisher : John Wiley & Sons
ISBN 13 : 1118752716
Total Pages : 288 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Quantile Regression by : Cristina Davino

Download or read book Quantile Regression written by Cristina Davino and published by John Wiley & Sons. This book was released on 2013-10-24 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensive description of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and followed by applications using real data. Quantile Regression: Presents a complete treatment of quantile regression methods, including, estimation, inference issues and application of methods. Delivers a balance between methodolgy and application Offers an overview of the recent developments in the quantile regression framework and why to use quantile regression in a variety of areas such as economics, finance and computing. Features a supporting website (www.wiley.com/go/quantile_regression) hosting datasets along with R, Stata and SAS software code. Researchers and PhD students in the field of statistics, economics, econometrics, social and environmental science and chemistry will benefit from this book.

Quantile Regression for Cross-Sectional and Time Series Data

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Publisher : Springer Nature
ISBN 13 : 3030445046
Total Pages : 63 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Quantile Regression for Cross-Sectional and Time Series Data by : Jorge M. Uribe

Download or read book Quantile Regression for Cross-Sectional and Time Series Data written by Jorge M. Uribe and published by Springer Nature. This book was released on 2020-03-30 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brief addresses the estimation of quantile regression models from a practical perspective, which will support researchers who need to use conditional quantile regression to measure economic relationships among a set of variables. It will also benefit students using the methodology for the first time, and practitioners at private or public organizations who are interested in modeling different fragments of the conditional distribution of a given variable. The book pursues a practical approach with reference to energy markets, helping readers learn the main features of the technique more quickly. Emphasis is placed on the implementation details and the correct interpretation of the quantile regression coefficients rather than on the technicalities of the method, unlike the approach used in the majority of the literature. All applications are illustrated with R.

Handbook of Quantile Regression

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Publisher : CRC Press
ISBN 13 : 1351646567
Total Pages : 739 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Handbook of Quantile Regression by : Roger Koenker

Download or read book Handbook of Quantile Regression written by Roger Koenker and published by CRC Press. This book was released on 2017-10-12 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 1970's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analysis, and longitudinal data. By focusing attention on local slices of the conditional distribution of response variables it is capable of providing a more complete, more nuanced view of heterogeneous covariate effects. Applications of quantile regression can now be found throughout the sciences, including astrophysics, chemistry, ecology, economics, finance, genomics, medicine, and meteorology. Software for quantile regression is now widely available in all the major statistical computing environments. The objective of this volume is to provide a comprehensive review of recent developments of quantile regression methodology illustrating its applicability in a wide range of scientific settings. The intended audience of the volume is researchers and graduate students across a diverse set of disciplines.

Quantile Regression

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Publisher : Wiley
ISBN 13 : 9781118863596
Total Pages : 0 pages
Book Rating : 4.8/5 (635 download)

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Book Synopsis Quantile Regression by : Marilena Furno

Download or read book Quantile Regression written by Marilena Furno and published by Wiley. This book was released on 2018-09-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains an overview of several technical topics of Quantile Regression Volume two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores topics including robustness, expectiles, m-quantile, decomposition, time series, elemental sets and linear programming. Graphical representations are widely used to visually introduce several issues, and to illustrate each method. All the topics are treated theoretically and using real data examples. Designed as a practical resource, the book is thorough without getting too technical about the statistical background. The authors cover a wide range of QR models useful in several fields. The software commands in R and Stata are available in the appendixes and featured on the accompanying website. The text: Provides an overview of several technical topics such as robustness of quantile regressions, bootstrap and elemental sets, treatment effect estimators Compares quantile regression with alternative estimators like expectiles, M-estimators and M-quantiles Offers a general introduction to linear programming focusing on the simplex method as solving method for the quantile regression problem Considers time-series issues like non-stationarity, spurious regressions, cointegration, conditional heteroskedasticity via quantile regression Offers an analysis that is both theoretically and practical Presents real data examples and graphical representations to explain the technical issues Written for researchers and students in the fields of statistics, economics, econometrics, social and environmental science, this text offers guide to the theory and application of quantile regression models.

Quantile Regression

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Publisher : John Wiley & Sons
ISBN 13 : 1118863593
Total Pages : 307 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Quantile Regression by : Marilena Furno

Download or read book Quantile Regression written by Marilena Furno and published by John Wiley & Sons. This book was released on 2018-09-24 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains an overview of several technical topics of Quantile Regression Volume two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores topics including robustness, expectiles, m-quantile, decomposition, time series, elemental sets and linear programming. Graphical representations are widely used to visually introduce several issues, and to illustrate each method. All the topics are treated theoretically and using real data examples. Designed as a practical resource, the book is thorough without getting too technical about the statistical background. The authors cover a wide range of QR models useful in several fields. The software commands in R and Stata are available in the appendixes and featured on the accompanying website. The text: Provides an overview of several technical topics such as robustness of quantile regressions, bootstrap and elemental sets, treatment effect estimators Compares quantile regression with alternative estimators like expectiles, M-estimators and M-quantiles Offers a general introduction to linear programming focusing on the simplex method as solving method for the quantile regression problem Considers time-series issues like non-stationarity, spurious regressions, cointegration, conditional heteroskedasticity via quantile regression Offers an analysis that is both theoretically and practical Presents real data examples and graphical representations to explain the technical issues Written for researchers and students in the fields of statistics, economics, econometrics, social and environmental science, this text offers guide to the theory and application of quantile regression models.

Essays on Estimating Distributional Continuous Treatment Effects

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Publisher :
ISBN 13 :
Total Pages : 370 pages
Book Rating : 4.:/5 (857 download)

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Book Synopsis Essays on Estimating Distributional Continuous Treatment Effects by :

Download or read book Essays on Estimating Distributional Continuous Treatment Effects written by and published by . This book was released on 2013 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: The unconditional distribution of potential outcomes with continuous treatments and the quantile structural function in a nonseparable triangular model can both be expressed as a partial mean process with generated regressors. In Chapter 1, I propose a multi-step nonparametric kernel-based estimator for this partial mean process. A uniform expansion reveals the influence of estimating the generated regressors on the final estimator. I focus on two examples of generated regressors (i) the generalized propensity score for a continuous treatment and (ii) the control variable in the nonseparable triangular models. By extending my results to Hadamard-differentiable functionals of the partial mean process, I am able to provide the limit distribution for estimating common inequality measures and various distributional features of the outcome variable. In the second chapter, I estimate the density-weighted Average Quantile Derivative (AQD), defined as the expectation of the partial derivative of the conditional quantile function (CQF) weighted by the density function of the covariates. The proposed estimator achieves root-n-consistency and asymptotic normality by a first-step nonparametric kernel estimation for the unknown functions and a second-step sample analogue of a full- mean. Therefore, the AQD summarizes the average marginal response of the covariates on the CQF and can be viewed as a nonparametric quantile regression coefficient. Similar to the widely studied average derivative in mean regression, the AQD identifies the coefficients up to scale in semiparametric single-index and partial linear models. In the third chapter, I allow for misspecification in the linear conditional quantile function (CQF) and calculate the semiparametric efficiency bound for the quantile regression (QR) parameter, the best linear predictor for a response variable under the asymmetric check loss function. As a result, the QR estimator developed by Koenker and Bassett (1978) semiparametrically efficiently estimates a pseudo-true parameter. The linear quantile projection model can be understood by the orthogonality condition of the covariates and the distribution error (i.e., the deviation of the true conditional distribution function, evaluated at the linearly approximated quantile, from the true probability).

Quantile Regression

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Publisher : John Wiley & Sons
ISBN 13 : 1119715180
Total Pages : 496 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Quantile Regression by : I. Gusti Ngurah Agung

Download or read book Quantile Regression written by I. Gusti Ngurah Agung and published by John Wiley & Sons. This book was released on 2021-06-18 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: QUANTILE REGRESSION A thorough presentation of Quantile Regression designed to help readers obtain richer information from data analyses The conditional least-square or mean-regression (MR) analysis is the quantitative research method used to model and analyze the relationships between a dependent variable and one or more independent variables, where each equation estimation of a regression can give only a single regression function or fitted values variable. As an advanced mean regression analysis, each estimation equation of the mean-regression can be used directly to estimate the conditional quantile regression (QR), which can quickly present the statistical results of a set nine QR(τ)s for τ(tau)s from 0.1 up to 0.9 to predict detail distribution of the response or criterion variable. QR is an important analytical tool in many disciplines such as statistics, econometrics, ecology, healthcare, and engineering. Quantile Regression: Applications on Experimental and Cross Section Data Using EViews provides examples of statistical results of various QR analyses based on experimental and cross section data of a variety of regression models. The author covers the applications of one-way, two-way, and n-way ANOVA quantile regressions, QRs with multi numerical predictors, heterogeneous QRs, and latent variables QRs, amongst others. Throughout the text, readers learn how to develop the best possible quantile regressions and how to conduct more advanced analysis using methods such as the quantile process, the Wald test, the redundant variables test, residual analysis, the stability test, and the omitted variables test. This rigorous volume: Describes how QR can provide a more detailed picture of the relationships between independent variables and the quantiles of the criterion variable, by using the least-square regression Presents the applications of the test for any quantile of any numerical response or criterion variable Explores relationship of QR with heterogeneity: how an independent variable affects a dependent variable Offers expert guidance on forecasting and how to draw the best conclusions from the results obtained Provides a step-by-step estimation method and guide to enable readers to conduct QR analysis using their own data sets Includes a detailed comparison of conditional QR and conditional mean regression Quantile Regression: Applications on Experimental and Cross Section Data Using EViews is a highly useful resource for students and lecturers in statistics, data analysis, econometrics, engineering, ecology, and healthcare, particularly those specializing in regression and quantitative data analysis.

Quantile Regression

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Publisher : SAGE Publications
ISBN 13 : 1483316904
Total Pages : 142 pages
Book Rating : 4.4/5 (833 download)

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Book Synopsis Quantile Regression by : Lingxin Hao

Download or read book Quantile Regression written by Lingxin Hao and published by SAGE Publications. This book was released on 2007-04-18 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile Regression, the first book of Hao and Naiman′s two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao and Naiman show, in their application of quantile regression to empirical research, how this model yields a more complete understanding of inequality. Inequality is a perennial concern in the social sciences, and recently there has been much research in health inequality as well. Major software packages have also gradually implemented quantile regression. Quantile Regression will be of interest not only to the traditional social science market but other markets such as the health and public health related disciplines. Key Features: Establishes a natural link between quantile regression and inequality studies in the social sciences Contains clearly defined terms, simplified empirical equations, illustrative graphs, empirical tables and graphs from examples Includes computational codes using statistical software popular among social scientists Oriented to empirical research

Quantile Regression

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Publisher : Cambridge University Press
ISBN 13 : 1139444719
Total Pages : 367 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Quantile Regression by : Roger Koenker

Download or read book Quantile Regression written by Roger Koenker and published by Cambridge University Press. This book was released on 2005-05-05 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.

Unconditional Quantile Regression for Panel Data with Exogenous Or Endogenous Regressors

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Unconditional Quantile Regression for Panel Data with Exogenous Or Endogenous Regressors by : David Powell

Download or read book Unconditional Quantile Regression for Panel Data with Exogenous Or Endogenous Regressors written by David Powell and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unconditional quantile treatment effects are difficult to estimate in the presence of fixed effects. Panel data are frequently used because fixed effects or differences are necessary to identify the parameters of interest. The inclusion of fixed effects or differencing of data, however, redefines the quantiles. This paper introduces a quantile estimator for panel data which conditions on fixed effects for identification but allows the parameters of interest to be interpreted in the same manner as cross-sectional quantile estimates. The quantile treatment effects are unconditional in the fixed effect but identification originates from differences in the covariates or instruments. The fixed effects are never estimated and the estimator is consistent for small T.

Recursive Estimation and Generated Regressors

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Publisher :
ISBN 13 : 9780864221742
Total Pages : 7 pages
Book Rating : 4.2/5 (217 download)

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Book Synopsis Recursive Estimation and Generated Regressors by : Michael McAleer

Download or read book Recursive Estimation and Generated Regressors written by Michael McAleer and published by . This book was released on 1992 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Quantile Regression

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Publisher :
ISBN 13 :
Total Pages : 77 pages
Book Rating : 4.:/5 (535 download)

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Book Synopsis Quantile Regression by : Roger Koenker

Download or read book Quantile Regression written by Roger Koenker and published by . This book was released on 1996 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Partial Mean Processes with Generated Regressors

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Publisher :
ISBN 13 :
Total Pages : 59 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Partial Mean Processes with Generated Regressors by : Ying-Ying Lee

Download or read book Partial Mean Processes with Generated Regressors written by Ying-Ying Lee and published by . This book was released on 2018 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: Partial mean with generated regressors arises in several econometric problems, such as the distribution of potential outcomes with continuous treatments and the quantile structural function in a nonseparable triangular model. This paper proposes a nonparametric estimator for the partial mean process, where the second step consists of a kernel regression on regressors that are estimated in the first step. The main contribution is a uniform expansion that characterizes in detail how the estimation error associated with the generated regressor affects the limiting distribution of the marginal integration estimator. The general results are illustrated with two examples: the generalized propensity score for a continuous treatment (Hirano and Imbens, 2004) and control variables in triangular models (Newey, Powell, and Vella, 1999; Imbens and Newey, 2009). An empirical application to the Job Corps program evaluation demonstrates the usefulness of the method.

Quantile Regression for Spatial Data

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Publisher : Springer Science & Business Media
ISBN 13 : 3642318150
Total Pages : 69 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Quantile Regression for Spatial Data by : Daniel P. McMillen

Download or read book Quantile Regression for Spatial Data written by Daniel P. McMillen and published by Springer Science & Business Media. This book was released on 2012-08-01 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable. Despite its advantages, quantile regression is still not commonly used in the analysis of spatial data. The objective of this book is to make quantile regression procedures more accessible for researchers working with spatial data sets. The emphasis is on interpretation of quantile regression results. A series of examples using both simulated and actual data sets shows how readily seemingly complex quantile regression results can be interpreted with sets of well-constructed graphs. Both parametric and nonparametric versions of spatial models are considered in detail.

Quantile Regression

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (131 download)

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Book Synopsis Quantile Regression by : Marilena Furno

Download or read book Quantile Regression written by Marilena Furno and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: