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Dynamic Panel Data Models [PDF]
, 2015 This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.
Bun, M.J.G., Sarafidis, V.
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Forecasting With Dynamic Panel Data Models [PDF]
Econometrica, 2020 This paper considers the problem of forecasting a collection of short time series using cross‐sectional information in panel data. We construct point predictors using Tweedie's formula for the posterior mean of heterogeneous coefficients under a correlated random effects distribution.
Liu, Laura +2 more
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ESTIMATING RICARDIAN MODELS WITH PANEL DATA [PDF]
Climate Change Economics, 2011 Although the Ricardian model is a cross sectional method, there are advantages to estimating the model with additional years of data. For instance, with a panel, one can more easily separate events in a single year (e.g. weather and price shocks) from longer term phenomenon such as climate.
EMANUELE MASSETTI, ROBERT MENDELSOHN
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Random Coefficient Panel Data Models [PDF]
SSRN Electronic Journal, 2004 This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random coefficients models and suggest a common framework for dealing with them. It considers the fundamental issues of statistical inference of a random coefficients formulation using both the sampling and Bayesian approaches.
Cheng Hsiao, M. Hashem Pesaran
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Nonlinear Panel Data Models [PDF]
, 2008 Panel or longitudinal data are becoming increasingly popular in applied work as they offer a number of advantages over pure cross-sectional or pure time-series data. A particularly useful feature is that they allow researchers to model unobserved heterogeneity at the level of the observational unit, where the latter may be an individual, a household, a
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Spatial Panel Data Models Using Stata [PDF]
SSRN Electronic Journal, 2016 xsmle is a new user-written command for spatial analysis. We consider the quasi–maximum likelihood estimation of a wide set of both fixed- and random-effects spatial models for balanced panel data. xsmle allows users to handle unbalanced panels using its full compatibility with the mi suite of commands, use spatial weight matrices in the form of both ...
BELOTTI, FEDERICO +2 more
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Frontiers in Environmental Science, 2022 Considering diverse national contexts, there are differences in the capacity of countries in terms of their ability to attain sustainability in its three main dimensions.
Simona-Roxana Ulman +5 more
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Subset-Continuous-Updating GMM Estimators for Dynamic Panel Data Models
Econometrics, 2016 The two-step GMM estimators of Arellano and Bond (1991) and Blundell and Bond (1998) for dynamic panel data models have been widely used in empirical work; however, neither of them performs well in small samples with weak instruments.
Richard A. Ashley, Xiaojin Sun
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Identifying inter-seasonal drought characteristics using binary outcome panel data models
Geocarto International, 2023 This study mainly focuses on spatiotemporal and inter-seasonal meteorological drought characteristics. Random Effect Logistic Regression Model (RELRM) and Conditional Fixed Effect Logistic Regression Model (CFELRM) are used to identify the spatiotemporal
Rizwan Niaz +5 more
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Estimating the substitution elasticities of import of factory industries using micro data and comparing long-term and short-term elasticities. [PDF]
پژوهشهای برنامه و توسعه, 2021 Estimating the substitution elasticity of imported products is a key parameter for analyzing trade policies, especially trade integration issues. In general, this elasticity represents the intensity of the impact of import demand on domestic demand from ...
Mehdi Yazdani, Mina Sadeghi
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