Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Paul Sicilian" <siciliap@gvsu.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: interpreting output from -xtivreg2- |

Date |
Mon, 08 Mar 2010 12:55:18 -0500 |

I have both economic and statistical questions regarding output from the user-written xtivreg2- command (available from ssc). I will state my questions up-front and then provide some background so that, hopefully, the questions will make sense. My questions are: 1) Are we interpreting the endogeneity tests provided by xtivreg2- correctly? 2) If yes to (1), do the combined results or our FE and IV/EGMM regressions (regarding children) make either economic or econometric sense to you? Background I am estimating ln(wage) regressions for married men on panel data. The r.h.s. variables of interest are wife's education, wife's work experience within the marriage and marriage duration (and some interactions among these variables). Some papers in this literature argue that wife's work experience is endogenous in the husband's wage equation and so use IV techniques with (i) family nonearned income, (ii) wife's age (and age squared) and (iii) various measures of the number of children in the household as instruments. I am dubious of using children as an instrument since children can affect time use within the marriage, which could affect men's wages. In (non-IV) FE (within person) estimations, I find a statistically significant (children) x (wife's work experience) interaction (and also a positive (children) x (wife's education) interaction effect (F-stat for the test of the joint significance of the children variables =3.05, pvalue=0.0276 )). I also use xtivreg2- to deal with the potential endogeneity of wife's work experience. Because of the FE results, I estimate some regressions using only family non-earned income, wife's age and wife's age squared as instruments. These instruments "pass" the endogeneity test using Sargen's J Statistic (p-values around 0.6), but they "fail" the weak instruments test (I am following the advice in Baum, Schaffer, and Stillmans Stata Journal (V. 7(4)) article and using the rule of thumb that the K-P F-statistic should be greater than 10. I am getting F-stats between 3 and 8, depending on sample and specification of the wage equation). However , if I include children (the actual variable is number of children in the household), the F-statistic for the test of weak instruments is about 67 and the J-test has a p-value still in the 0.6 range. Moreover, I use the -orthog- option to calculate the C-statistic for just the children instrument and that has a p-value around 0.4. My understanding is that these results imply that children are a legitimate instrument, seeming to contradict the FE estimates that suggest children affect mens wages. Below is an example of an -xtivreg2- command I use (with children as an instrument) and the(abbreviated) output from that command. Thanks for your consideration. -Paul . xtivreg2 lwage sp_ed educ tenure tenure2 exper exper2 current spedcurrent urban south ncent west yr2-yr23 mine-ind_nr pro-occ_nr (sp_years = V_total sp_age sp_age2 childhh) if male==1 & white==1 & married==1 & wage2006>1 & wage2006 < 400 & self!=1 & ag~=1 /// & farmer~=1 & farmlab~=1 & army!=1 & current~=0 & sp_ed~=0 & yearmarried>1977, gmm2s robust fe orthog(childhh) . . FIXED EFFECTS ESTIMATION Number of groups = 1498 Obs per group: min = 2 avg = 5.2 max = 13 2-Step GMM estimation Estimates efficient for arbitrary heteroskedasticity Statistics robust to heteroskedasticity Number of obs = 7765 F( 43, 6224) = 94.65 Prob > F = 0.0000 Total (centered) SS = 769.5200468 Centered R2 = 0.3975 Total (uncentered) SS = 769.5200468 Uncentered R2 = 0.3975 Residual SS = 463.6217297 Root MSE = .272 . . (output omitted) . Underidentification test (Kleibergen‐Paap rk LM statistic): 223.938 Chi-sq(4) P-val = 0.0000 Weak identification test (Kleibergen‐Paap rk Wald F statistic): 67.877 Stock-Yogo weak ID test critical values: 5% maximal IV relative bias 16.85 10% maximal IV relative bias 10.27 20% maximal IV relative bias 6.71 30% maximal IV relative bias 5.34 10% maximal IV size 24.58 15% maximal IV size 13.96 20% maximal IV size 10.26 25% maximal IV size 8.31 Source: Stock‐Yogo (2005). Reproduced by permission. NB: Critical values are for Cragg‐Donald F statistic and i.i.d. errors. Hansen J statistic (overidentification test of all instruments): 1.617 Chi-sq(3) P‐val = 0.6554 -orthog- option: Hansen J statistic (eqn. excluding suspect orthog. conditions): 1.066 Chi-sq(2) P-val = 0.5869 C statistic (exogeneity/orthogonality of suspect instruments): 0.552 Chi-sq(1) P-val = 0.4576 Instruments tested: childhh * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: interpreting output from -xtivreg2-***From:*Austin Nichols <austinnichols@gmail.com>

- Prev by Date:
**st: decompose string** - Next by Date:
**st: RE: decompose string** - Previous by thread:
**st: decompose string** - Next by thread:
**Re: st: interpreting output from -xtivreg2-** - Index(es):