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Panel Data Econometrics Empirical Applications

Langue : Anglais

Coordonnateur : Tsionas Mike

Couverture de l’ouvrage Panel Data Econometrics

Panel Data Econometrics:  Empirical Applications introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illuminate applications for a variety of fields, such as banking, financial markets, tourism and transportation, auctions, and experimental economics. Contributors emphasize techniques and applications, and they accompany their explanations with case studies, empirical exercises and supplementary code in R. They also address panel data analysis in the context of productivity and efficiency analysis, where some of the most interesting applications and advancements have recently been made.

13. Capital Regulation, Efficiency, and Risk Taking: A Spatial Panel Analysis of U.S. Banks14. Panel Data in Educational Research15. Panel Data in Energy Economics16. Panel Data Analysis Based on Lab Evidence in Auction Market Experiments 17. Maximum Likelihood for Cross-Lagged Panel Models With Fixed Effects18. Panel Data in Transportation Research19. Panel Data in Banking: Research Issues and Data Peculiarities 20. Quantile Panel Estimation of Financial Contagion Effects 21. Application of Panel Data Models for Empirical Economic Analysis 22. The Income-Health Gradient: Evidence From Self-Reported Health and Biomarkers in Understanding Society23. Application in Banking: Securitization and Global Banking24. Regional Innovation in the United States: A Poisson Stochastic Frontier Approach With Finite Mixture Structure 25. Making Inference of British Household’s Happiness Efficiency: A Panel Bayesian Inference Procedure26. The Impact of Explicit Deposit Insurance on Market Discipline 27. Export Pricing at the Firm Level With Panel Data 28. The Relationship Between Economic Growth and Democracy: Alternative Representations of Technological Change 29. Analysis of Stochastic Dominance Ranking of Chinese Income Distributions by Household Attributes30. The Neural Network Production Function: Panel Evidence for the United States

Early career researchers in econometrics and other fields including banking, financial markets, tourism and transportation, auctions, experimental economics who seek to adopt econometric techniques for research in their specific application environments. Practitioners seeking a stronger footing for empirical studies. Graduate students and 1st year PhD students of economics, econometrics, and statistics looking to implement the formal skillset learned in volume one

Mike G. Tsionas is Professor of Economics in the Lancaster University Management School (Ph.D, 1994, University of Minnesota). He is a Fellow of the Journal of Econometrics, a Distinguished Author of the Journal of Applied Econometrics and an Associate Editor of Empirical Economics, Journal of Productivity Analysis, Economic Modelling, Journal of Mathematics and the Journal of Banking and Finance in the past. He has authored several books and 160 academic papers in such journals as Review of Economic Studies, Journal of the American Statistical Association, Journal of Econometrics, Journal of Applied Econometrics, Operations Research, European Journal of Operational Research, Journal of Economic Dynamics and Control, Journal of Banking and Finance, and several other leading Economics journals.
  • Provides a vast array of empirical applications useful to practitioners from different application environments
  • Accompanied by extensive case studies and empirical exercises
  • Includes empirical chapters accompanied by supplementary code in R, helping researchers replicate findings
  • Represents an accessible resource for diverse industries, including health, transportation, tourism, economic growth, and banking, where researchers are not always econometrics experts

Date de parution :

Ouvrage de 1011 p.

15x22.8 cm

Disponible chez l'éditeur (délai d'approvisionnement : 14 jours).

122,46 €

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Mots-clés :

Aggregate; Airlines; Applications; Artificial neural networks; Auction; Bank lending channel; Bank risk; Bayesian inference; Biomarkers; British households; China; Cost functions; Cross-lagged panel models; Democracy; Distance functions; Dummy variables; Dynamic panel data models; Economic growth; Education; Efficiency; Electric utilities; Estimation; Expenditure; Financial frictions; Financial safety net design; Firm exporting; Firm fixed effects; Fixed effects; Flexible adjustment speed; General index; Global banking; GMM estimation; Happiness efficiency; Health inequalities; Heterogeneity; Implicit or explicit deposit insurance; Income distribution; Inequality; Innovation; Latent modeling; Long-run income; Market discipline by depositors; Markups; Methodology; Metropolitan; Mixture; ML estimation; Mobility; Monetary transmission; Monte Carlo study; Multiple time trends; Nonparametric testing; Panel data; Panel data models; Panel estimation; Panel regression; Poisson stochastic frontier; Political economy of financial sector regulation; Pricing; Probit model; Problems and solutions in using banking data; Production function; Production functions; Profit functions; Quality; Quantile regression; Railroads; Regional; Regression; Securitization; Shadow costs; Single time trend; Spatial error model; Spatial weight matrix; States; Stochastic dominance; survey of empirical banking studies; Systemic risk; Target level of GDP; Technical efficiency; Technology shifters; Total factor productivity; Understanding Society: the UK Household Longitudinal Study; Welfare ranking

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