{"title":"实证的方法","authors":"","doi":"10.1017/9781108290234.005","DOIUrl":null,"url":null,"abstract":"(c) Standard errors: If εt are independent over time. 1. OLS standard errors α̂i, β̂i. 2. λ̂ : σ(λ̂) = σ(ft) √ T (d) Test α are jointly zero? 1. Answer: look at α̂0cov(α̂, α̂0)−1α̂. Precise forms, α̂0cov(α̂)−1α̂ = T £ 1 + f̄ 0Σ−1 f f̄ ¤−1 α̂Σα̂ ̃χN T −N −K N £ 1 + f̄ 0Σ−1 f f̄ ¤−1 α̂Σ̂α̂ ̃FN,T−N−K Intuition. R t = αi + β 0 ift + ε i t means that α̂i ≈ α + 1 T PT t=1 ε i t (except for beta fitting). Thus cov(α̂) ≈ 1 T Σ. The other terms correct for beta fitting. As usual χ is asymptotic for any iid distribution, F is finite-sample for normal ε.","PeriodicalId":150054,"journal":{"name":"An Introduction to Geographical and Urban Economics","volume":"49-50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Empirical Methods\",\"authors\":\"\",\"doi\":\"10.1017/9781108290234.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"(c) Standard errors: If εt are independent over time. 1. OLS standard errors α̂i, β̂i. 2. λ̂ : σ(λ̂) = σ(ft) √ T (d) Test α are jointly zero? 1. Answer: look at α̂0cov(α̂, α̂0)−1α̂. Precise forms, α̂0cov(α̂)−1α̂ = T £ 1 + f̄ 0Σ−1 f f̄ ¤−1 α̂Σα̂ ̃χN T −N −K N £ 1 + f̄ 0Σ−1 f f̄ ¤−1 α̂Σ̂α̂ ̃FN,T−N−K Intuition. R t = αi + β 0 ift + ε i t means that α̂i ≈ α + 1 T PT t=1 ε i t (except for beta fitting). Thus cov(α̂) ≈ 1 T Σ. The other terms correct for beta fitting. As usual χ is asymptotic for any iid distribution, F is finite-sample for normal ε.\",\"PeriodicalId\":150054,\"journal\":{\"name\":\"An Introduction to Geographical and Urban Economics\",\"volume\":\"49-50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"An Introduction to Geographical and Urban Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/9781108290234.005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"An Introduction to Geographical and Urban Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/9781108290234.005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
(c) Standard errors: If εt are independent over time. 1. OLS standard errors α̂i, β̂i. 2. λ̂ : σ(λ̂) = σ(ft) √ T (d) Test α are jointly zero? 1. Answer: look at α̂0cov(α̂, α̂0)−1α̂. Precise forms, α̂0cov(α̂)−1α̂ = T £ 1 + f̄ 0Σ−1 f f̄ ¤−1 α̂Σα̂ ̃χN T −N −K N £ 1 + f̄ 0Σ−1 f f̄ ¤−1 α̂Σ̂α̂ ̃FN,T−N−K Intuition. R t = αi + β 0 ift + ε i t means that α̂i ≈ α + 1 T PT t=1 ε i t (except for beta fitting). Thus cov(α̂) ≈ 1 T Σ. The other terms correct for beta fitting. As usual χ is asymptotic for any iid distribution, F is finite-sample for normal ε.