Titlebook: Applied Econometric Analysis Using Cross Section and Panel Data; Deep Mukherjee Book 2023 The Editor(s) (if applicable) and The Author(s),

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https://doi.org/10.1007/978-1-4020-6226-1se or outcome) variable takes values which are discrete and inherently ordered. Within this setting, the dependent variable may take only two values (such as 0 and 1) giving rise to binary models (e.g., probit and logit) or more than two values (say ., where . is a small integer) giving rise to ordi

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L. Bornatici,C. Ciaponi,S. Papiritile regression using rich nutrition data from rural India. The unique feature of estimating parameters at various quantiles of the distribution has several advantages: (a) it allows analyzing the relationship between variables beyond the mean; (b) it allows analyzing variables that are not independ

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https://doi.org/10.1007/978-3-030-88292-1ous functional forms, which can produce biased estimates. Most empirical studies in economics use parametric specifications to analyze the linear relationship between the dependent and independent variables of interest. Semi- or nonparametric regression models offer a significant advance, as they al

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Giovanni Maciocco,Silvia Serreli increasing need to model several and mixed (dependent) variables in a system, either as a system seemingly unrelated regressions, or in a more general system of simultaneous equations. However, few econometric models have been developed to handle such empirical questions and many other complex deve

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Giovanni Maciocco,Silvia Serrelind its extension the multivariate Tobit model which is essentially a Seemingly Unrelated Regression or multi-equation Tobit system. The model is illustrated through an empirical application on technology adoption problem in agriculture. In developing countries, failures of programs to formulate tech