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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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發(fā)表于 2025-3-30 11:18:09 | 只看該作者
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發(fā)表于 2025-3-30 13:19:20 | 只看該作者
CONVERGENCE Architecture a Concise Overview,egressors other than the spatial or time lag in the dependent variable This chapter presents a new method to estimate this kind of model, called Spatial Dynamic Limited Information Maximum Likelihood (SDLIML), when some exploratory variables are endogenous. A Monte Carlo simulation shows that this e
53#
發(fā)表于 2025-3-30 16:41:22 | 只看該作者
https://doi.org/10.1007/978-3-319-95013-6terogeneous and asymmetric effect in modeling the long panel data. The chapter will then demonstrate the application using country-level data from Southeast and South Asia. ARDL and NARDL models are estimated using EViews and Stata to examine how the global commodity prices and each sub-agriculture
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發(fā)表于 2025-3-30 23:02:41 | 只看該作者
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發(fā)表于 2025-3-31 04:27:59 | 只看該作者
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發(fā)表于 2025-3-31 06:00:48 | 只看該作者
Count Data Regression: Modeling Diversification in Sports Participation in Spainndard versions used in the microeconometric literature (Poisson and Negative Binomial models) and extending these basic models by considering different specifications in terms of how the zeros are generated. Finally, specific attention is devoted to the interpretation of the estimated coefficients a
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發(fā)表于 2025-3-31 09:49:01 | 只看該作者
Binary and Ordinal Probit Regression: Applications to Public Opinion on Marijuana Legalization in thFollowing the theoretical overview, we utilize the binary and ordinal models to analyze public opinion on marijuana legalization and the extent of legalization in the United States. All computations are done in MATLAB. We obtain several interesting results including that past use of marijuana, belie
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發(fā)表于 2025-3-31 17:24:40 | 只看該作者
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發(fā)表于 2025-3-31 17:55:54 | 只看該作者
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