全部版块 我的主页
论坛 数据科学与人工智能 数据分析与数据科学 SAS专版
8673 9
2005-05-17
<P>怎么在SAS中进行panel数据分析</P>
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

全部回复
2005-5-18 05:41:00

Among those statistical packages that excel in programs for panel data analysis are LIMDEP, STATA, and SAS. Although all three packages have procedures dedicated to panel data analysis, LIMDEP and STATA appear to have a particularly rich variety of panel analytic procedures. All three packages have fixed and random effects models, can handle balanced or unbalanced panels, and have one- or two-way random and fixed effects models. Although LIMDEP and STATA have the both Hausman and Sargan tests for specification, SAS has only the Hausman specification test. Both LIMDEP and STATA have the Hausman and Taylor estimator for random effects. All three packages have procedures that can correct for autocorrelation in the models. LIMDEP and STATA have Arellano, Bond and Bover's estimator for dynamic panel models, whereas SAS uses the Parks method. LIMDEP, STATA, and SAS procedures can handle groupwise heteroskedasticity in the random effects model. LIMDEP and STATA have the Hildreth, Houck, and Swamy random coefficients model. Stata has xtreg for performing a random coefficient analysis with only a random intercept. When more than one random coefficient has to be analyzed, one can use the gllamm (generalized linear latent and mixed models) procedure (Twisk, 2003). SAS can perform this kind of analysis with its Mixed procedure. STATA and LIMDEP have procedures for panel corrected standard errors. SAS has a variance component moving average (De Silva) procedure.

http://www.nyu.edu/its/pubs/connect/fall03/yaffee_primer.html

二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2005-5-18 05:41:00

References

Davidson, R. and MacKinnon, J.G. (1993). Estimation and Inference in Econometrics. New York: Oxford University Press, pp. 320, 323.

Greene, W. H. (2002). LIMDEP, version 8.0. Econometric Modeling Guide, Vol 1. Plainview, NY: Econometric Software, Inc., pp.E14-9 - E14-11.

Greene, W. H. (2003). Econometric Analysis. 5th ed. Upper Saddle River: Prentice Hall, pp. 285, 291, 293, 304.

Greenberg, D. Longitudinal Data Analysis, personal communication, September 6, 2003, referring to the research of Nathaniel Beck.

Gujarati, D. (2003). Basic Econometrics. 4th ed. New York: McGraw Hill, pp. 638-640.

Greene, W. H. (2003). LIMDEP Version 8 Econometric Modeling Guide, Vol. 1. Plainview, NY: Econometric Software, pp. E8_1-E8_98; E8_26-E8_30.

Powell, J. and Chay, K. (2003). Semiparametric Censored Regression Models. Downloaded from World Wide Web, September 21, 2003) from http://elsa.berkeley.edu/~kenchay/ftp/binresp/jepfinal.pdf.

SAS Institute (1999). SAS User's Guide, Version 8. Vol 2. Cary, NC: SAS Institute. pp. 1111, 1113, 1114.

Sayrs, L. (1989). Pooled Time Series Analysis. Newbury Park, Ca: Sage, pp.10, 32.

Stata (2003). Cross-Sectional Time Series. College Station, Texas: Stata Press, pp. 10, 62, 93, 224.

Twisk, Jos. W. (2003). Applied Longitudinal Data Analysis for Epidemiology. New York: Cambridge University Press. pp. 250-251.

Woolridge, J. (2002). Econometric Analysis of Cross-Section and Panel Data. MIT Press, pp. 130, 279, 420-449.

[此贴子已经被作者于2005-5-18 5:46:44编辑过]

二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2005-5-18 05:43:00

Longitudinal and Panel Data: Analysis and Applications for the Social Sciences

SAS

Stata

R

Chapter Title

Chapter 1

Divorce Analysis

Divorce Analysis

Divorce Analysis

Introduction

Chapter 2

Medicare Analysis

Medicare Analysis

Medicare Analysis

Fixed Effects Models

Section 2.4.3

*Influence Diagnostics

Section 2.4.4

*Cross-Sectional Correlations

Chapter 3

Taxprep Analysis

Taxprep Analysis

Taxprep Analysis

Models with Random Effects

Chapter 4 Section 4.1

ANOVA Model Predictions

Prediction and Bayesian Inference

Section 4.5

Lottery Exploration

Lottery Exploration

Lottery Exploration

Section 4.5

*Lottery In-Sample Analysis

Lottery In-Sample Analysis

Lottery In-Sample Analysis

Section 4.5

Lottery Out-of-Sample Analysis

Section 4.5

*Lottery Forecasting

Chapter 5 Section 5.2

Dental Analysis

Dental Analysis

Dental Analysis

Multilevel Models

Chapter 6 Section 6.2 & 6.3

Taxprep Endogeneity Analysis

Arellano-Bond Linear, Dynamic Panel Data Estimator

Stochastic Regressors

Chapter 7

Taxprep Analysis

Taxprep Analysis

Taxprep Analysis

Modeling Issues

Chapter 8 Section 8.6

Insurance Beta

Insurance Beta

Insurance Beta

Dynamic Models

Section 8.6

*CAPM Kalman Filter Estimation

Section 8.6

*CAPM Prediction

Chapter 9

Tax Preparer

Tax Preparer

Tax Preparer

Binary Dependent Variables

Chapter 10

Tort Filings

Tort Filings

Tort Filings

Generalized Linear Models

Chapter 11

Yogurt Choice

Tax Preparer Choice

Yogurt Choice

Yogurt Choice

Categorical Dependent Variables and Survival Models

Supplemental Information

Summary of Commands

Summary of Commands

Summary of Commands

二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2005-5-18 05:45:00
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

2005-5-18 05:47:00
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

点击查看更多内容…
相关推荐
栏目导航
热门文章
推荐文章

说点什么

分享

扫码加好友,拉您进群
各岗位、行业、专业交流群