Deneme Sınavı Soruları

What distinguishes a weighted price index from an unweighted price index?

Which of the following best describes seasonal variation in a time series?

Using time series data consisting of 100 observations, the autocorrelations for the first and second lags are estimated as 0.3 and 0.2. Which of the following is the estimation value of the partial autocorrelation coefficient for the lag one?

I. R² is overstated giving the impression of a well-fitted model

II. The t and F tests are overstated, and prone to rejecting the null hypothesis even if it is correct

III. The OLS estimates of the standard errors of coefficients are unbiased

Which of the given could be among the consequences of serial correlation?

How are ARMA(p,q) models typically identified in time series analysis?

I. The 2SLS method addresses the endogeneity problem by using instrumental variables (IVs) to proxy for the endogenous variables and identify the causal effect more accurately.

II. The 2SLS method is unusable when dealing with simultaneous equations models where there is endogeneity and simultaneous causation between variables.

III. The two-stage least squares method is an essential tool in econometrics for addressing endogeneity and obtaining reliable estimates of causal relationships. 

What can be said to be true about the Two-Stage Least Squares method (2SLS)?

I. It is a common issue in statistical and econometric analysis that arises when the explanatory variable(s) used in a regression model are correlated with the error term or disturbance in the model. 

II.  The correlation between the explanatory variable(s) used in a regression model and the error term or disturbance violates the assumption of exogeneity, which is a key assumption for obtaining unbiased and consistent parameter estimates in regression analysis.

III. In simple terms, endogeneity bias occurs when there is a one-way causal relationship between the independent variable and one or more regressors, making it difficult to determine the true cause-and-effect relationship.

What can be said to be true about the endogeneity bias?

I. The explanatory variables must be controlled by the experimenter (non-stochastic) which is never the case.

II.  The model that is tested must include an intercept.

III. It only tests for second-order autocorrelation in the residuals in models with lagged dependent variables.

What can be said to be true about the Durbin Watson (DW) d-test?

What is the situation where one or more variables used in a statistical analysis are measured imprecisely or with error?

I. Generalized Least Squares

II. Model Specification

III. Non-Linear Models

Which of the given can be used to deal with a model with heteroskedasticity?

Which of the given functions could be a linear regression model?

In an ARIMA(p, d, q) model, what does the 'd' represent?

I. According to the Gauss-Markov theorem, have the least variance among the class of estimators that are linear and unbiased. 

II. The minimum variance of an OLS estimator indicates it is the most efficient estimator as it provides the tightest estimates around the population value of the parameter.

III. According to the Gauss-Markov theorem, have the least variance among the class of estimators that are non-linear and biased. 

What can be said to be true about the OLS estimators?

Which of the following is a key concept in time series analysis that implies statistical properties remain constant over time?

Using time series data consisting of 100 observations, the autocorrelations for the first and second lags are estimated as 0.5 and 0.325. Which of the following is the estimation value of the partial autocorrelation coefficient for the lag two?

I. LM-test

II. Model Specification

III. Robust Standard Errors

Which of the given can be used to deal with a model with serially correlated residuals?

What is the main purpose of the partial autocorrelation function (PACF) in time series analysis?