family, social or networking responsibilities. Short-term traders might opt to shout orders from thetradingfloor early in the morning. Position traders might decide to wait until the close to place orders, or come in a half-hour before the close. Day traders can create their...
We also ran the PROCESS models once with and once without heteroskedasticity-consistent inference (HC3). As the pattern of results was consistent across all the analyses, we report the outcomes of the ANOVAs and regular PROCESS models. We initially controlled, in all analyses and with dummy ...
To estimate an ARCH (Autoregressive Conditional Heteroskedasticity) model, what is used: *a. The Ordinary Least Squared Method (OLS) *b. The Maximum Likelihood Estimation Method (MLE) *c. The generalized method of moments *d. All of the above A) C...
In our analysis, we have adjusted the standard errors for heteroskedasticity using a Windmeijer correction. The results of the SYS GMM method are reported in Table 8. Consistent with what is reported in Table 7, we continue to find that when real estate prices are experiencing a bubble, ...
The study contrasted using the latest ARDL procedure to handle any potential effects. In order to circumvent problems with the dependent variable being a number in order 0, we first employed the augmented ARDL model proposed by Anser et al. [89]. To address the impact of positive and ...
FGLS is the best strategy for dealing with heteroskedasticity. The ordinary least square (OLS) approach may become inefficient when the variance of the independent variables is not equal because the findings are confusing, causing estimators to make inaccurate assumptions. The FGLS model is divided ...
To avoid the effects of extreme values, we applied a top and bottom 1% tail shrinkage (Winsorisation) to all continuous variables at the firm level. To control for potential heteroskedasticity and serial correlation problems, the standard errors of all regression coefficients in this study were ...
Thus, a moderate non-normality and a moderate heteroskedasticity characterize the residuals. Nevertheless, we believe the sample size is large enough for an approximated asymptotic normality of the estimates and a correct interpretation of p-values....
Our standard errors were robust to heteroskedasticity. We estimated three model specifications. The first specification focuses on the effect of intrinsic motivation on the likelihood of being a user-innovator. In this step and all other model specifications, we included the level of technical ...