Gautam Tripathi – författare

This volume of Advances in Econometrics contains a selection of papers presented at the "Econometrics of Complex Survey Data: Theory and Applications" conference organized by the Bank of Canada, Ottawa, Canada, from October 19-20, 2017. The papers included in this volume span a range of methodological and practical topics including survey collection comparisons, imputation mechanisms, the bootstrap, nonparametric techniques, specification tests, and empirical likelihood estimation using complex survey data. For academics and students with an interest in econometrics and the ways in which complex survey data can be used and evaluated, this volume is essential.

This volume of Advances in Econometrics contains a selection of papers presented at the "Econometrics of Complex Survey Data: Theory and Applications" conference organized by the Bank of Canada, Ottawa, Canada, from October 19-20, 2017. The papers included in this volume span a range of methodological and practical topics including survey collection comparisons, imputation mechanisms, the bootstrap, nonparametric techniques, specification tests, and empirical likelihood estimation using complex survey data. For academics and students with an interest in econometrics and the ways in which complex survey data can be used and evaluated, this volume is essential.

This volume of Advances in Econometrics contains a selection of papers presented at the "Econometrics of Complex Survey Data: Theory and Applications" conference organized by the Bank of Canada, Ottawa, Canada, from October 19-20, 2017. The papers included in this volume span a range of methodological and practical topics including survey collection comparisons, imputation mechanisms, the bootstrap, nonparametric techniques, specification tests, and empirical likelihood estimation using complex survey data. For academics and students with an interest in econometrics and the ways in which complex survey data can be used and evaluated, this volume is essential.

This book provides a new contemporary time series approach for econometrics and finance. In a concrete manner a very general divergence between spectra is introduced, resulting in the development of a statistical inference that is efficient and robust, and leads to a new perspective. A measure of systemic risk is also developed in the energy market,which quantifies the cost of energy asset distress vis-à-vis the broader economy during crises, and examines the dynamic interaction between solvency and funding liquidity risk in banks using a panel vector autoregressive (VAR) model. This step shows that a forward-looking measure of capital shortfall under stress is both a predictor and an outcome of funding liquidity risk. Additionally, a new integrated likelihood-based approach for estimating nonlinear panel data models is described. Unlike existing integrated likelihoods, the new integrated likelihood is closer to a genuine likelihood. The book explains why this is due to first-order information unbiasedness, and why it seems to matter more for inference than for estimation. Results of studies in econometrics are provided for support.