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Pravin K Trivedi - One of the best experts on this subject based on the ideXlab platform.

  • Microeconometrics using stata revised edition
    2010
    Co-Authors: Colin A Cameron, Pravin K Trivedi
    Abstract:

    A complete and up-to-date survey of microeconometric methods available in Stata, Microeconometrics Using Stata, Revised Edition is an outstanding introduction to Microeconometrics and how to execute microeconometric research using Stata. It covers topics left out of most Microeconometrics textbooks and omitted from basic introductions to Stata. This revised edition has been updated to reflect the new features available in Stata 11 that are useful to microeconomists. Instead of using mfx and the user-written margeff commands, the authors employ the new margins command, emphasizing both marginal effects at the means and average marginal effects. They also replace the xi command with factor variables, which allow you to specify indicator variables and interaction effects. Along with several new examples, this edition presents the new gmm command for generalized method of moments and nonlinear instrumental-variables estimation. In addition, the chapter on maximum likelihood estimation incorporates enhancements made to ml in Stata 11. Throughout the book, the authors use simulation methods to illustrate features of the estimators and tests described and provide an in-depth Stata example for each topic discussed. They also show how to use Statas programming features to implement methods for which Stata does not have a specific command. The unique combination of topics, intuitive introductions to methods, and detailed illustrations of Stata examples make this book an invaluable, hands-on addition to the library of anyone who uses microeconometric methods.

  • Microeconometrics using stata revised edition
    Stata Press books, 2010
    Co-Authors: Colin A Cameron, Pravin K Trivedi
    Abstract:

    Microeconometrics Using Stata, Revised Edition, by A. Colin Cameron and Pravin K. Trivedi, is an outstanding introduction to Microeconometrics and how to do microeconometric research using Stata. Aimed at students and researchers, this book covers topics left out of Microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata. The revised edition has been updated to reflect the new features available in Stata 11 that are germane to microeconomists. Instead of using mfx and the user-written margeff commands, the revised edition uses the new margins command, emphasizing both marginal effects at the means and average marginal effects. Factor variables, which allow you to specify indicator variables and interaction effects, replace the xi command. The new gmm command for generalized method of moments and nonlinear instrumental-variables estimation is presented, along with several examples. Finally, the chapter on maximum likelihood estimation incorporates the enhancements made to ml in Stata 11.

  • Microeconometrics using stata
    2009
    Co-Authors: Colin A Cameron, Pravin K Trivedi
    Abstract:

    An outstanding introduction to Microeconometrics and how to do microeconometric research using Stata, this book covers topics often left out of Microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata. They begin by introducing simulation methods and then use them to illustrate features of the estimators and tests described in the rest of the book. They address each topic with an in-depth Stata example and demonstrate how to use Statas programming features to implement methods for which Stata does not have a specific command. Multi/Card Deck Copy

  • empirical Microeconometrics selected examples
    2009
    Co-Authors: David T Jachochavez, Pravin K Trivedi
    Abstract:

    The substance and style of modern Microeconometrics is shaped by its role in analyses of public policy issues. Computational considerations have proved to be an important influence on the methodology and scope of empirical analyses that address these issues. To be convincing to a wide readership the empirical analyses need to be based on representative data and flexible modeling approaches. In this chapter we illustrate, through a variety of empirical examples, how modelers handle the complexities that arise from the richness of survey data and the heterogeneity in behavior of market participants. After introductory sections on data and programming languages, the remainder of the chapter covers many leading computationally intensive econometric techniques. These are illustrated by means of specific numerical examples. An algorithmic format is used to describe the computational features.

  • computational considerations in empirical Microeconometrics selected examples
    Palgrave Macmillan Books, 2009
    Co-Authors: David T Jachochavez, Pravin K Trivedi
    Abstract:

    The substance and style of modern Microeconometrics is shaped by its role in analyses of public policy issues. Computational considerations have proved to be an important influence on the methodology and scope of empirical analyses that address these issues. To be convincing to a wide readership the empirical analyses need to be based on representative data and flexible modeling approaches. In this chapter we illustrate, through a variety of empirical examples, how modelers handle the complexities that arise from the richness of survey data and the heterogeneity in behavior of market participants. After introductory sections on data and programming languages, the remainder of the chapter covers many leading computationally intensive econometric techniques. These are illustrated by means of specific numerical examples. An algorithmic format is used to describe the computational features.

Colin A Cameron - One of the best experts on this subject based on the ideXlab platform.

  • In preparation for a special issue of the Stata Journal.
    2014
    Co-Authors: Colin A Cameron
    Abstract:

    This article discusses how Microeconometrics research has evolved since 1985, the year Stata was released, and how Stata has been part of this process

  • Microeconometrics and stata over the past thirty years
    2014
    Co-Authors: Colin A Cameron
    Abstract:

    This article discusses how Microeconometrics research has evolved since 1985, the year Stata was released, and how Stata has been part of this process.

  • Microeconometrics using stata revised edition
    2010
    Co-Authors: Colin A Cameron, Pravin K Trivedi
    Abstract:

    A complete and up-to-date survey of microeconometric methods available in Stata, Microeconometrics Using Stata, Revised Edition is an outstanding introduction to Microeconometrics and how to execute microeconometric research using Stata. It covers topics left out of most Microeconometrics textbooks and omitted from basic introductions to Stata. This revised edition has been updated to reflect the new features available in Stata 11 that are useful to microeconomists. Instead of using mfx and the user-written margeff commands, the authors employ the new margins command, emphasizing both marginal effects at the means and average marginal effects. They also replace the xi command with factor variables, which allow you to specify indicator variables and interaction effects. Along with several new examples, this edition presents the new gmm command for generalized method of moments and nonlinear instrumental-variables estimation. In addition, the chapter on maximum likelihood estimation incorporates enhancements made to ml in Stata 11. Throughout the book, the authors use simulation methods to illustrate features of the estimators and tests described and provide an in-depth Stata example for each topic discussed. They also show how to use Statas programming features to implement methods for which Stata does not have a specific command. The unique combination of topics, intuitive introductions to methods, and detailed illustrations of Stata examples make this book an invaluable, hands-on addition to the library of anyone who uses microeconometric methods.

  • Microeconometrics using stata revised edition
    Stata Press books, 2010
    Co-Authors: Colin A Cameron, Pravin K Trivedi
    Abstract:

    Microeconometrics Using Stata, Revised Edition, by A. Colin Cameron and Pravin K. Trivedi, is an outstanding introduction to Microeconometrics and how to do microeconometric research using Stata. Aimed at students and researchers, this book covers topics left out of Microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata. The revised edition has been updated to reflect the new features available in Stata 11 that are germane to microeconomists. Instead of using mfx and the user-written margeff commands, the revised edition uses the new margins command, emphasizing both marginal effects at the means and average marginal effects. Factor variables, which allow you to specify indicator variables and interaction effects, replace the xi command. The new gmm command for generalized method of moments and nonlinear instrumental-variables estimation is presented, along with several examples. Finally, the chapter on maximum likelihood estimation incorporates the enhancements made to ml in Stata 11.

  • Microeconometrics using stata
    2009
    Co-Authors: Colin A Cameron, Pravin K Trivedi
    Abstract:

    An outstanding introduction to Microeconometrics and how to do microeconometric research using Stata, this book covers topics often left out of Microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata. They begin by introducing simulation methods and then use them to illustrate features of the estimators and tests described in the rest of the book. They address each topic with an in-depth Stata example and demonstrate how to use Statas programming features to implement methods for which Stata does not have a specific command. Multi/Card Deck Copy

Marina Furdas - One of the best experts on this subject based on the ideXlab platform.

  • Problem Set 3 Minimum Wage in a Natural Experiment Preparations
    2015
    Co-Authors: Marina Furdas
    Abstract:

    Materials for the first tutorial in Microeconometrics (problem set, data etc.) are available on L:\Microeconometrics WS1415\Exercise 3. Please do not use the L-drive as your work station! Instead, create for the exercise session in this course a new folder with your name in directory T: \ and copy the content from L:\Microeconometrics WS1415\ into your folder. Exercise 1: Estimating the Effect of a Minimum Wage Change on Employment Read in the data set “minwage.raw ” into Stata. It contains the following variables in the given order: Variable name Variable descriptio

  • 2 Propensity Score Matching with the NSW Data
    2015
    Co-Authors: Marina Furdas
    Abstract:

    Materials for the first tutorial in Microeconometrics (problem set, data etc.) are available on L:\Microeconometrics WS1415\Exercise 2. Please do not use the L-drive as your work station! Instead, create for the exercise session in this course a new folder with your name in directory T: \ and copy the content from L:\Microeconometrics WS1415\ into your folder. 1 Review of the Potential Outcome Approach Assume that in an ideal world, we could observe potential outcomes Y0 and Y1 for both treated and untreated. Persons 1, 2 and 3 are untreated (D = 0), persons 4 and 5 are treated (D = 1). person Y1 Y0

  • Exercise 1: Estimating the Effect of Training Programs on Earnings using Propensity Score Matching
    2013
    Co-Authors: Marina Furdas
    Abstract:

    Materials for the 3rd tutorial in Microeconometrics (problem set, data etc.) are available on L:\Microeconometrics WS1213\Tutorial 3. Please do not use the L-drive as your work station! Instead, create for the exercise session in this course a new folder with your name in directory T: \ and copy the content from L:\Microeconometrics WS1213\ into your folder

  • Problem Set 4 Minimum Wage in a Natural Experiment
    2013
    Co-Authors: Pd Dr. Alexander Spermann, Marina Furdas
    Abstract:

    Materials for the 4th tutorial in Microeconometrics (problem set, data etc.) are available on L:\Microeconometrics WS1213\Tutorial 4. Please do not use the L-drive as your work station! Instead, create for the exercise session in this course a new folder with your name in directory T: \ and copy the content from L:\Microeconometrics WS1213\ into your folder. Exercise 1: Estimating the Effect of a Minimum Wage Change on Employment Read in the data set “minwage.raw ” into TSP. It contains the following variables in the given order: Variable name Variable descriptio

  • Problem Set 6 Regression Discontinuity Design
    2013
    Co-Authors: Pd Dr. Alexander Spermann, Marina Furdas
    Abstract:

    Materials for the 6th tutorial in Microeconometrics (problem set, data etc.) are available on L:\Microeconometrics WS1213\Tutorial 6. Please do not use the L-drive as your work station! Instead, create for the exercise session in this course a new folder with your name in directory T: \ and copy the content from L:\Microeconometrics WS1213\ into your folder. Exercise 1: Estimating the effect of party incumbency based on RD analysis The problem set focuses on measuring the electoral advantage of incumbency using data from the Lee’s (2008) paper: “Randomized experiments from non–random selection in U.S. House elections”. Data consists of the following variables: Variable name Variable description mov Democratic vote share margin of victory, election t demsharenext Democrat vote share, election t + 1 demshareprev Democrat vote share, election t demwinprev Dummy (=1 if Democratic party won, election t) demofficeexp Democrat political experience, as of election t demelectexp Democrat electoral experience, as of election t othofficeexp Opposition political experience, as of election t othelectexp Opposition electoral experience, as of election t statedisdec State–district–decade clusters Lee (2008) aims at estimating the incumbency advantage in elections to the U.S. House of Representatives at the Congressional district level. The identification strategy relies on comparing districts where Democratic party barely won an election – and hence barely became an incumbent – with districts where Democratic party barely lost (and a Republican party won). The outcome variable of interest is the party’s vote share in subsequent election. All variables are defined for the Democratic party only

Hanwen Ning - One of the best experts on this subject based on the ideXlab platform.

  • deep tobit networks a novel machine learning approach to Microeconometrics
    Neural Networks, 2021
    Co-Authors: Jiaming Zhang, Xinyuan Song, Hanwen Ning
    Abstract:

    Abstract Tobit models (also called as “censored regression models” or classified as “sample selection models” in Microeconometrics) have been widely applied to microeconometric problems with censored outcomes. However, due to their linear parametric settings and restrictive normality assumptions, the traditional Tobit models fail to capture the pervading nonlinearities and thus may be inadequate for microeconometric analysis with large-scale datasets. This paper proposes two novel deep neural networks for Tobit problems and explores machine learning approaches in the context of microeconometric modeling. We connect the censored outputs in Tobit models with some deep learning techniques, which are thought to be unrelated to Microeconometrics, and use the rectified linear unit activation and a particularly designed network structure to implement the censored output mechanisms and realize the underlying econometric conceptions. The benchmark Tobit-I and Tobit-II models are then reformulated as two carefully designed deep feedforward neural networks named deep Tobit-I network and deep Tobit-II network, respectively. A novel significance testing method is developed based on the proposed networks. Compared with the traditional models, our networks with deep structures can effectively describe the underlying highly nonlinear relationships and achieve considerable improvements in fitting and prediction. With the novel testing method, the proposed networks enable highly accurate and sophisticated econometric analysis with minimal random assumptions. The encouraging numerical experiments on synthetic and realistic datasets demonstrate the utility and advantages of the proposed method.

Steven Ongena - One of the best experts on this subject based on the ideXlab platform.

  • Microeconometrics of banking methods applications and results
    2009
    Co-Authors: Hans Degryse, Moshe Kim, Steven Ongena
    Abstract:

    INTRODUCTION WHY DO FINANCIAL INTERMEDIARIES EXIST? THE INDUSTRIAL ORGANIZATION APPROACH TO BANKING THE LENDER-BORROWER RELATIONSHIP EQUILIBRIUM AND RATIONING IN THE CREDIT MARKET THE MACROECONOMIC CONSEQUENCES OF FINANCIAL IMPERFECTIONS INDIVIDUAL BANK RUNS AND SYSTEMIC RISK MANAGING RISKS IN THE BANKING FIRM THE REGULATION OF BANKS CONCLUSION EPILOGUE: THE BANKING CRISIS OF 2007-2008

  • Microeconometrics of banking methods applications and results
    Research Papers in Economics, 2009
    Co-Authors: Hans Degryse, Moshe Kim, Steven Ongena
    Abstract:

    This book provides a compendium to the empirical work investigating the hypotheses generated by recent banking theory. Such a compendium is overdue. Since the publication of the The Microeconomics of Banking by Xavier Freixas and Jean Charles Rochet, work in empirical banking has further blossomed, not only in sheer volume but also in the variety of questions being tackled, datasets becoming available, and methodologies being introduced. This book follows the structure in Freixas and Rochet's book and arranges the relevant methodologies, applications, and results according to each of their original chapters in order to have a coherent synthesis between available theory and supporting empirics. Each chapter in Microeconometrics of Banking contains a modest introduction (where possible and appropriate), a concise methodology section with one or more relevant methodologies, and several illustrative applications. In a "muscular" results section the authors summarize the main robust and seminal findings in the literature that are in the text, and provide the details of many other studies in figures and tables. Available in OSO: http://www.oxfordscholarship.com/oso/public/content/economicsfinance/9780195340471/toc.html