MC for Final

MC for Final - Chapter 12 Introduction to Time Series...

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1 Chapter 12 Introduction to Time Series Regression and Forecasting Multiple Choice 1) Pseudo out-of-sample forecasting can be used for the following reasons with the exception of a. giving the forecaster a sense of how well the model forecasts at the end of the sample. b. estimating the RMSFE. c. analyzing whether or not a time series contains a unit root. d. evaluating the relative forecasting performance of two or more forecasting models. 2) Autoregressive distributed lag models include a. current and lagged values of the error term. b. lags of the dependent variable, and lagged values of additional predictor variables. c. current and lagged values of the residuals. d. lags and leads of the dependent variable. 3) Time series variables fail to be stationary when a. the economy experiences severe fluctuations. b. the population regression has breaks. c. there is strong seasonal variation in the data. d. there are no trends. 4) Departures from stationarity a. jeopardize forecasts and inference based on time series regression. b. occur often in cross-sectional data. c. can be made to have less severe consequences by using log-log specifications. d. cannot be fixed. 5) In order to make reliable forecasts with time series data, all of the following conditions are needed with the exception of
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2 a. coefficients having been estimated precisely. b. the regression having high explanatory power. c. the regression being stable. d. the presence of omitted variable bias. 6) The first difference of the logarithm of Y t equals a. the first difference of Y . b. the difference between the lead and the lag of Y . c. approximately the growth rate of Y when the growth rate is small.
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MC for Final - Chapter 12 Introduction to Time Series...

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