The Experts below are selected from a list of 18 Experts worldwide ranked by ideXlab platform
Silvana Tenreyro - One of the best experts on this subject based on the ideXlab platform.
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Trading Partners and Trading Volumes: Implementing the Helpman-Melitz-Rubinstein Model Empirically
2026Co-Authors: J. Santos M. C. Silva, Silvana TenreyroAbstract:Helpman, Melitz, and Rubinstein (2008)-HMR-present a rich theoretical model to study the determinants of bilateral trade flows across countries. The model is then empirically implemented through a two-stage estimation procedure. This note seeks to clarify some econometric aspects of the estimation approach used by HMR and explore the consequences of possible departures from the maintained distributional assumptions.Gravity equation, Heteroskedasticity, Jensens Inequality
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Further Simulation Evidence on the Performance of the Poisson Pseudo-Maximum Likelihood Estimator
2026Co-Authors: J. Santos M. C. Silva, Silvana TenreyroAbstract:We extend the simulation results given in Santos-Silva and Tenreyro (2006, 'The Log of Gravity', The Review of Economics and Statistics, 88, pp.641-658) by considering data generated as a finite mixture of gamma variates. Data generated in this way can naturally have a large proportion of zeros and is fully compatible with constant elasticity models such as the gravity equation. Our results confirm that the Poisson pseudo maximum likelihood estimator is generally well behaved.Gravity equation, Heteroskedasticity, Jensens Inequality
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The Log of Gravity
2026Co-Authors: Joao Santos Silva, Silvana TenreyroAbstract:Although economists have long been aware of Jensen's Inequality, many econometric applications have neglected an important implication of it: the standard practice of interpreting the parameters of log-linearized models estimated by ordinary least squares as elasticities can be highly misleading in the presence of heteroskedasticity. This paper explains why this problem arises and proposes an appropriate estimator. Our criticism to conventional practices and the solution we propose extends to a broad range of economic applications where the equation under study is log-linearized. We develop the argument using one particular illustration, the gravity equation for trade, and apply the proposed technique to provide new estimates of this equation. We find significant differences between estimates obtained with the proposed estimator and those obtained with the traditional method. These discrepancies persist even when the gravity equation takes into account multilateral resistance terms or fixed effectsElasticities, Gravity equation, Heteroskedasticity, Jensens Inequality, Poisson regression, Preferential-trade agreements
J. Santos M. C. Silva - One of the best experts on this subject based on the ideXlab platform.
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Trading Partners and Trading Volumes: Implementing the Helpman-Melitz-Rubinstein Model Empirically
2026Co-Authors: J. Santos M. C. Silva, Silvana TenreyroAbstract:Helpman, Melitz, and Rubinstein (2008)-HMR-present a rich theoretical model to study the determinants of bilateral trade flows across countries. The model is then empirically implemented through a two-stage estimation procedure. This note seeks to clarify some econometric aspects of the estimation approach used by HMR and explore the consequences of possible departures from the maintained distributional assumptions.Gravity equation, Heteroskedasticity, Jensens Inequality
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Further Simulation Evidence on the Performance of the Poisson Pseudo-Maximum Likelihood Estimator
2026Co-Authors: J. Santos M. C. Silva, Silvana TenreyroAbstract:We extend the simulation results given in Santos-Silva and Tenreyro (2006, 'The Log of Gravity', The Review of Economics and Statistics, 88, pp.641-658) by considering data generated as a finite mixture of gamma variates. Data generated in this way can naturally have a large proportion of zeros and is fully compatible with constant elasticity models such as the gravity equation. Our results confirm that the Poisson pseudo maximum likelihood estimator is generally well behaved.Gravity equation, Heteroskedasticity, Jensens Inequality
Joao Santos Silva - One of the best experts on this subject based on the ideXlab platform.
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The Log of Gravity
2026Co-Authors: Joao Santos Silva, Silvana TenreyroAbstract:Although economists have long been aware of Jensen's Inequality, many econometric applications have neglected an important implication of it: the standard practice of interpreting the parameters of log-linearized models estimated by ordinary least squares as elasticities can be highly misleading in the presence of heteroskedasticity. This paper explains why this problem arises and proposes an appropriate estimator. Our criticism to conventional practices and the solution we propose extends to a broad range of economic applications where the equation under study is log-linearized. We develop the argument using one particular illustration, the gravity equation for trade, and apply the proposed technique to provide new estimates of this equation. We find significant differences between estimates obtained with the proposed estimator and those obtained with the traditional method. These discrepancies persist even when the gravity equation takes into account multilateral resistance terms or fixed effectsElasticities, Gravity equation, Heteroskedasticity, Jensens Inequality, Poisson regression, Preferential-trade agreements
Fuad E Alsaadi - One of the best experts on this subject based on the ideXlab platform.
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design of extended dissipativity state estimation for generalized neural networks with mixed time varying delay signals
Information Sciences, 2018Co-Authors: R Manivannan, R Samidurai, Jinde Cao, Ahmed Alsaedi, Fuad E AlsaadiAbstract:This paper investigates the issue of extended dissipativity state estimation of generalized neural networks (GNNs) with mixed time-varying delay signals. The integral terms in the time derivative of the LyapunovKrasovskii functionals (LKFs) are estimated by the famous Jensens Inequality, reciprocally convex combination (RCC) approach together with the Wirtinger double integral Inequality (WDII) technique. In addition, in order to estimate the double integral terms in the derivative of the LKF, a new integral Inequality is proposed. As a result, a new delay-dependent criterion is derived under which the estimated error system is extended dissipative. The concept of extended dissipativity state estimation can be applied to deal with the L2L state estimation, H state estimation, passivity state estimation, mixed H and passivity state estimation, (Q,S,R)-dissipativity state estimation of GNNs by choosing the weighting matrices. The advantage of the proposed method is demonstrated by five numerical examples, among them one example was supported by real-life application of the benchmark problem that is associated with reasonable issues in the sense of an extended dissipativity performance.
R Manivannan - One of the best experts on this subject based on the ideXlab platform.
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design of extended dissipativity state estimation for generalized neural networks with mixed time varying delay signals
Information Sciences, 2018Co-Authors: R Manivannan, R Samidurai, Jinde Cao, Ahmed Alsaedi, Fuad E AlsaadiAbstract:This paper investigates the issue of extended dissipativity state estimation of generalized neural networks (GNNs) with mixed time-varying delay signals. The integral terms in the time derivative of the LyapunovKrasovskii functionals (LKFs) are estimated by the famous Jensens Inequality, reciprocally convex combination (RCC) approach together with the Wirtinger double integral Inequality (WDII) technique. In addition, in order to estimate the double integral terms in the derivative of the LKF, a new integral Inequality is proposed. As a result, a new delay-dependent criterion is derived under which the estimated error system is extended dissipative. The concept of extended dissipativity state estimation can be applied to deal with the L2L state estimation, H state estimation, passivity state estimation, mixed H and passivity state estimation, (Q,S,R)-dissipativity state estimation of GNNs by choosing the weighting matrices. The advantage of the proposed method is demonstrated by five numerical examples, among them one example was supported by real-life application of the benchmark problem that is associated with reasonable issues in the sense of an extended dissipativity performance.