| 来源类型 | Working Paper
|
| 规范类型 | 报告
|
| DOI | 10.3386/w20374
|
| 来源ID | Working Paper 20374
|
| Spatial Errors in Count Data Regressions |
| Marinho Bertanha; Petra Moser
|
| 发表日期 | 2014-08-14
|
| 出版年 | 2014
|
| 语种 | 英语
|
| 摘要 | Count data regressions are an important tool for empirical analyses ranging from analyses of patent counts to measures of health and unemployment. Along with negative binomial, Poisson panel regressions are a preferred method of analysis because the Poisson conditional fixed effects maximum likelihood estimator (PCFE) and its sandwich variance estimator are consistent even if the data are not Poisson-distributed, or if the data are correlated over time. Analyses of counts may be affected by correlation in the cross-section. For example, patent counts or publications may increase across related research fields in response to common shocks. This paper shows that the PCFE and its sandwich variance estimator are consistent in the presence of such dependence in the cross-section - as long as spatial dependence is time-invariant. In addition to the PCFE, this result also applies to the commonly used Logit model of panel data with fixed effects. We develop a test for time-invariant spatial dependence and provide code in STATA and MATLAB to implement the test. |
| 主题 | Econometrics
; Estimation Methods
; Development and Growth
; Innovation and R&
; D
|
| URL | https://www.nber.org/papers/w20374
|
| 来源智库 | National Bureau of Economic Research (United States)
|
| 引用统计 |
|
| 资源类型 | 智库出版物
|
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/578048
|
推荐引用方式
GB/T 7714 |
Marinho Bertanha,Petra Moser. Spatial Errors in Count Data Regressions. 2014.
|
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