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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Binary and Ordinal Probit Regression: Applications to Public Opinion on Marijuana Legalization in thse 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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Random Logit Model: An Application to?US Soft Drink Differentiated Demand Estimationso known as the BLP model. The chapter discusses reasons for the BLP’s superiority over traditional demand models, such as the AIDS models. It also describes recent development in the BLP-type literature, especially dealing with computational issues. In addition, the chapter covers the empirical pro

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Quantile Regression and Decomposition Techniques: An Application to Nutritional Demand in Indiatile 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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Mixture Models: Identifying Consumption Classes in Post-liberalization Indiall population, without any information about the membership of individuals in the sub-populations or even the number of sub-populations. In this chapter, I present the theory of mixture models, and an application in which I identify consumption classes in urban India in 1999–00 (NSS). Suppose there

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Nonparametric and Semiparametric Regressions: An Empirical Investigation of Engel’s Law in the Conteous 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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A Primer on Spatial Regression Models: Applications to Poverty and Inequality of Indian Districts is questionable whenever the units of analysis are spatially dependent. The first step for capturing spatial dependence is to define a spatial weight matrix, where the matrix elements capture pairwise spatial dependence between the units of analysis. Given the weight matrix, two main models that ev

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Hurdle Regression Models: An Application to Consumer Behavior in?the?United Statesture surveys. These models are of particular interest to explain the presence of a large proportion of zero observations for the dependent variable by means of censoring mechanisms, called hurdles. For the analysis of censored household expenditure data, up to three hurdles, expressing, respectively

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Multivariate Tobit Model: An Application to Farmer Adoption of Soil Erosion Practices in El Salvadornd 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