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Group variable: idcode Number of groups = 4,434Ĭorr(u_i, X) = 0 (assumed) Prob > chi2 =. Random-effects GLS regression Number of obs = 26,200 Time variable: year, 70 to 88, but with gaps
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I then ran the Hausman test which I understand as indicating that I should be using a fixed effect rather than random effect model: yield) as the dependent variable and only BIDASKSP (Liquidity) as the independent variable to isolate the fixed-effect estimator Pi (as outlined in the equation above)? Is it correct to run xtreg with YIELDDIFF (i.e. Am I interpreting this test correctly as saying that my fixed-effect estimator has an explanatory value for the yield of the bonds, as given by u_i=0: F(165, 44584) = 1130.58 - and that I should in fact use a fixed effect model? What does the large F value mean?Ģ. Group variable: RIC_2 Number of groups = 166 I have first run an F-test, with the following result:įixed-effects (within) regression Number of obs = 44,751 Y_i,t = P_i+Liquidity_i,t +e_i,t with e being the error term. Yield has variable name YIELDDIFF and Liquidity is BIDASKSP The regression I am trying to perform is: (Y is yield, P_i is the fixed-effect estimator, Liquidity is the variable for Liquidity). I am not sure if I am interpreting the results of these tests correctly and what my model choice should be going forward to perform regressions in stata. So far I have run various tests to check whether I should use a fixed or random effects model, as well as tests to check for autocorrelation and heteroskedasticity, as well as an F-test. More specifically, I am trying to run a regression of the yield on a measure of the bond's liquidity to find the unobserved effect that isn't explained by the variable liquidity. My goal is to run a regression that shows what variables have an effect on the bond's yield. I have about 54 000 observations of bond yields. ISI DARI BUKU INI JUGA SUDAH DIBUAT DENGAN STANDAR KUALITAS YANG TINGGI SEHINGGA DIHARAPKAN DAPAT MENJADI PEGANGAN BAGI PARA PENELITI, MAHASISWA MAUPUN DOSEN PENGAMPU MATA KULIAH STATISTIK.I have a large set of panel data with information about 166 bonds, containing some of their characteristics (such as currency, issue date, etc.) followed by daily yield data over a five year period for each bond (although most of these values are missing). BUKU INI DITULIS DENGAN TUJUAN UNTUK MENGISI KEKOSONGAN LITERATUR BUKU STATA YANG ADA DI INDOENSIA DAN DILUAR NEGERI PROGRAM STATA SANGAT POPULAR DIGUNAKAN DI BERBAGAI UNIVERSITAS TERNAMA. STATA JUGA SUDAH TERINTEGRASI DENGAN R PEKCAGES DAN MEMPUNYAI TAMPILAN GRAFIK YANG LUAR BIASA. MENGAPA? KARENA SELAIN MENYEDIAKAN FITUR ANALISIS MULTIVARIAT YANG KOMPLIT, STATA JUGA DAPAT DIGUNAKAN UNTUK SEM, BAYESIAN, MULTILEVEL MODELING DAN BAHKAN FITUR TIME-SERIES NYA ITU SERUPA DENGAN EVIEWS. BAGI YANG BELUM MENGENAL PROGRAM STATA, PERLU DIKETAHUI BAHWA STATA MERUPAKAN PROGRAM STATISTIK YANG SANGAT LENGKAP DAN POWERFUL.
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SAYA INGIN MENGINFORMASIKAN BAHWA TELAH TERBIT BUKU BARU YANG BERJUDUL "APLIKASI ANALISIS DATA STATISTIK UNTUK ILMU SOSIAL SAINS DENGAN STATA" BUKU INI TERDIRI DARI DUA VOLUME, YAITU UNTUK VOLUME 1 MEMBAHAS TENTANG ANALISIS UNIVARIAT, MULTIVARIAT, PARAMETRIK DAN NON-PARAMETRIK SERTA SAMPLING, POPULASI, VALIDITAS, RELIABILITAS DAN SEBAGAINYA (BUKUNYA SUDAH TERBIT SAAT INI DAN DAFTAR ISINYA DAPAT DILIHAT PADA ATTACH FILE) DAN VOLUME 2 AKAN MEMBAHAS TENTANG SEM, BAYESIAN DAN MULTILEVEL MODELING (SEDANG DI PROSES). PLS Structural Equation Modeling (PLS-SEM) 15 Oktober 2014 21.10