计量经济学Test bank questions Chapter 5

multiple choice test bank questions no feedbackchapter 5correct answers denoted by an asterisk。1.consider the following model estimated for a time seriesYt=0.3 0.5 yt-1-0.4 ET-1 etWhere et is a zero mean error process。what is the(unconditional)mean of the series，yt？(a) * 0.6(b) 0.3(c) 0.0(d) 0.42.consider the following single exponential smoothing model :St=a Xt (1-a) St-1you are given the following data :=0.1；Xt=0.5；St-1=0.2if we believe that the true DGP can be approximated by the exponential smoothing model，what would be an appropriate 2-step ahead forecast forecast(i.e. a forecast of Xt 2 made at time t)(a) 0.2(b) * 0.23(c) 0.5(d)there is insufficient information given in the question to form more than a one step ahead forecast。3.consider the following ma(3)process。yt=0 . 1 0 . 4 ut-1 0 . 2 ut-20 . 1 ut-3 utWhat is the optimal forecast for yt，3 steps into the future(I . e . for time t 2 if all information until time t-1 is available)，ifut-1=0.3；ut-2=-0.6；Ut-3=-0.3(a) 0.4(b) 0.0(c) * 0.07(d)0.14.which of the following sets of character istics would usually best describe an auto regiressive process of order 3(I . e . an ar(3)？(a) * a slowly decaying ACF，and a pacf with 3 significant spikes(b)a slowly decaying pacf and ACF with 3 significant spikes(c) A slowly decaying ACF and pacf(d)an ACF and a pacf with 3 significant spikes5.a process，XT，which has a constant mean and variance，and zero auto covariance for all non-zero lags is best described as(a) * A white noise process(b) co variance stationary process(c) An autocorrelated process(d)移动平均流程6.which of the following conditions must hold for the auto regressive part of an ARMA model to be stationary？(a)* all roots of the character istic equation must lie outside the unit circle(b)all roots of the character istic equation must lie inside the unit circle(c)all roots must be smaller than unity(d)at least one of the roots must be bigger than one in absolute value。7.which of the following statements are true concerning time-series forecasting？(I)all time-series forecasting methods are essential ly extra polative。(ii)forecasting models are prone to perform poorly following a structural break in a series。(iii)forecasting accuracy offen declines with prediction horizon。(iv)the mean squared errors of forecasts are usually highly correlated with the profitability of employing those forecasts in a trading strading(a) (i)、(ii)、(iii)、和(iv)(b) * (i)，(ii) and (iii) only(c) (ii)，(iii) only(d) (ii) and (iv) only8.if a series，yt，follows a random walk (with no drift)，what is the optimal 1-step ahead forecast for y？(a) * the current value of Y .(b)零。(c)the historical unweighted average of y(d)an exponentilly weighted average of previous values of y9.consider a series that follows an ma(1)with zero mean and a moving average coefficient of 0.4。what is the value of the auto correlation function at lag 1？(a) 0.4(b) 1(c) *0.34(d)it is not possible to determine the value of the auto covariances without knoving the disturbance variance。10.which of the following statements are true？(I)an ma(q)can be expressed as an ar(ra infinity)if it is invertable(ii)an ar(p)can be written as an ma(ra infinity)if it is stationary(iii)the(unconditional)mean of an ARMA process will depend only on the intercept and on the ar coefficients and not on the ma coefficents(iv)random walk series will have zero pacf except at lag 1(a) (ii) and (iv) only(b) (i) and (iii) only(c) (i)、(ii)、and (iii) only(d) * (i)、(ii)、(iii)、和(iv)。11.consider the following picture and suggest the model from the following list that best character sises the process 3360(a) An AR(1)(b) An AR(2)(c) * An ARMA(1，1)(d) An MA(3)the ACF is clearly declining very slowly in this case，Which is conistent with their being an auto regiressive part to the appropriate model .the pacf is clearaly sigificant for lags one and two，But the question is does it them become insignificant for lags 2 and 4，indicating an arWell，given the huge size of the sample that gave rise to this ACF and pacf，Even a pacf value of 0.001 would still be statistally significant . TTthe DGP for the data That generated this plotwas y _ t=0.9y _(t-1)0.3 u _(t-1)u _ t12.which of the following models can be estimated using ordinary least squares？(i) An AR(1)(ii) ARMA (2，0)(iii) An MA(1)(iv) ARMA (1，1)(a) (i) only(b) * (i) and (ii) only(c) (i)、(ii)、and (iii) only(d) (i)、(ii)、(iii)、和(iv)。13.if a series，y，is descripd as“mean-reverting”，which model from the following list is likey to produce the best long-term from(a) A random walk(b) * The long term mean of the series(c) A model from the ARMA family(d) random walk with drift14.consider the following ar (2) model。what is the optimal 2-step ahead forecast for y If all information available is up to and including time t，If the values of y at time t，t-tYt=-0.1 0.75yt-1-0.125yt-2 ut(a) -0.1(b) 0.27(c) * -0.34(d) 0.3015.wha