idiosyncratic component, common component has a smaller variance than the idiosyncratic component: [e.sub.it]~N(0,1) and r= [theta]/2.
Note that estimates from the log-2SLS model were re-transformed into dollars with a homoskedastic
nonparametric retransformation (Duan 1983).
However, in our case, errors are homoskedastic
and sample size is small, so IV technique with fixed effect is the most suitable technique.
Model 1 also passes all diagnostic tests, indicating that the residuals are not serially correlated5 (LM test), are normally distributed (Jarque-Bera test), and homoskedastic
where [[??].sub.t] [equivalent to] [A.sub.t][[lambda].sub.t] and [[alpha].sub.t] = [A.sub.t]/[A.sub.t-1] = exp([alpha] + [[epsilon].sub.t]), [alpha] > 0, and [[epsilon].sub.t] is the mean zero, homoskedastic
TFP shock innovation.
t-ratio ONE 0,1076 0,8319 LNKI 0,0180 1,6721 LOGPIBPC (0,0361) (1,2171) TDCPOP (1,1254) (1,3006) VIP 0,0007 1,9498 Homoskedastic
Regression (S0) Nonautocorrelated disturbances (RO) Pooled OLS residual variance (SS/nT) 0,0006 Test statistics for homoscedasticity: Deg.Ft.=17 C*(.95) = 27.59 C * (.99) = 33,4100 Lagtange multiplier statistic = 31,1163 Log-likelihood function = 122,9044 Wald statistic = Likelihood ratio statistic = Estimacion: MCG Estimator = 2 Step GLS Regresion 5 Coeff.
Under the additional assumption that asset returns and consumption are jointly log normal and homoskedastic
, the Epstein-Zin Euler equation implies that the risk premium RP on any asset i over the short-term safe asset is
The null hypothesis that the errors are homoskedastic
was rejected for the regressions with both a dummy variable for positive and for negative returns.
where [[bar [sdebt.sub.i]], is the average (across years) secured debt-to-total debt ratio for firm i, [bar [X'.sub.i]], is a vector of control variables averaged across years, (89) [bar [tort.sub.i]] is an indicator variable for whether or not the firm is a high-tort-risk firm (several different measures of this risk are used), (90) and [[epsilon].sub.i] is a normally distributed, homoskedastic
error term that is uncorrelated with the regressors.
The 4 lag VAR has no significant residual autocorrelation; the Jarque-Bera statistic indicates normality of residuals and the White test for heteroskedasticity indicates homoskedastic
Spatial error dependence, which may be caused by spatial correlation of omitted variables or spatial mismatch in data measurement, violates the standard assumptions of the linear regression model (e.g., the assumption of independent, homoskedastic
By contrast, for the Tobit model, a standard MLE technique to estimate equations with censored dependent variables, the consistency hinges on the assumption of normally distributed and homoskedastic