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Titlebook: Econometrics in Theory and Practice; Analysis of Cross Se Panchanan Das Book 2019 Springer Nature Singapore Pte Ltd. 2019 Econometrics.Cros

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樓主: deliberate
11#
發(fā)表于 2025-3-23 10:30:42 | 只看該作者
12#
發(fā)表于 2025-3-23 15:34:27 | 只看該作者
Analysis of Collinear Data: Multicollinearityxamines the regression model when the assumption of independence among the independent variables is violated. The concept of multicollinearity and its consequences on the least squares estimators are explained. The detection of multicollinearity and alternatives for handling the problem are also discussed in this chapter.
13#
發(fā)表于 2025-3-23 20:03:35 | 只看該作者
Multivariate Analysisivariate analysis very briefly. We discuss here mainly the principal component analysis, factor analysis and multivariate regression analysis. The techniques are widely used in empirical research in different areas with cross section data.
14#
發(fā)表于 2025-3-24 00:14:55 | 只看該作者
Unconditional Jumps and Keyboard Input,the basis of the estimates from the known sample. In classical econometrics, the principal way of doing this is performing hypothesis tests and constructing confidence intervals. This chapter deals with this problem.
15#
發(fā)表于 2025-3-24 04:16:04 | 只看該作者
16#
發(fā)表于 2025-3-24 08:52:17 | 只看該作者
https://doi.org/10.1007/978-3-7091-8756-2 A dummy variable which is binary in nature is used to represent qualitative information in a linear regression model. This chapter explains how qualitative explanatory variables can be incorporated into a linear model.
17#
發(fā)表于 2025-3-24 12:56:27 | 只看該作者
Differences in Sexual Orientationn addition to being interested in the contemporaneous relationships among such variables, we are often concerned with relationships between their current and past values. This chapter discusses data generating process of time series data and how time series data are generated.
18#
發(fā)表于 2025-3-24 18:50:22 | 只看該作者
19#
發(fā)表于 2025-3-24 18:59:43 | 只看該作者
20#
發(fā)表于 2025-3-24 23:16:38 | 只看該作者
ty, the regression coefficients for an ordinary least squares regression are still unbiased, but the standard errors and confidence intervals estimated by conventional procedures will be large, giving a false sense of precision. This chapter examines the behaviour of volatility in terms of conditional heteroscedasticity model.
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