Additive model; Adaptive response rate; AIC (Akaike's Information Criterion); Algorithm; Applicability; ARMA model; ARIMA; Asymptotically unbiased estimator; Autocorrelated errors; Autocorrelation; Autocorrelation function; Autoregressive (AR) model; Backcasting; Backward shift operator; Biased estimator; BIC (Bayesian Information Criterion); Box-Jenkins methodology; Box-Pierce test; Business cycle; Census II; Central limit theorem; Chi-square test; Classical decomposition method; Coefficient of determination; Coefficient of variation; Confidence interval; Correlation coefficient; Correlation matrix; Correlogram; Covariance; Critical value; Crosscorrelation; Cumulative forecasting; Curve fitting; Cyclical data; Cyclical index; Decomposition; Degrees of freedom (df); Delphi method; Dependent variable; Depression; Deseasonalized data; Diagnostic checking; Differencing; Double moving average; Dummy variable; Durbin-Watson statistic; Dynamic regression models; Econometric model; Economic indicator; Elasticity; Endogenous variable; Error; Error cost function; Estimation; Ex ante forecast; Ex post forecast; Exogenous variable; Explanatory model; Explanatory variable; Exploratory forecasting; Exponential growth; Exponential smoothing; Feedback; File; Filter; First difference; Forecasting; Forecast horizon; Forecast interval; Forecast variable; Fourier analysis; F-test; Function; Goodness of fit; Gross National Product (GNP); Heteroscedasticity; Heuristic; Holdout set; Holt's exponential smoothing method; Holt-Winters' exponential smoothing method; Homoscedasticity; Horizontal or stationary data; Hypothesis testing; Identification; Impulse response weights; Independent variable; Index numbers; Indicator variable; Integrated; Interactive forecasting; Intercept; Interdependence; Intervention analysis; Lag; Lead; Leading indicator; Lead time; Least squares estimation; Likelihood; Ljung-Box test; Local regression; Loess; Logistic curve; Logarithmic transformation; Macrodata; Matrix; Maximum likelihood estimation; M-Competition; M3-IJF Competition; Mean; Mean Absolute Percentage Error (MAPE); Mean Percentage Error (MPE); Mean Squared Error (MSE); Medial average; Median; Microdata; Mixed model; Model; Moving average; Multicollinearity; Multiple correlation coefficient; Multiple regression; Multiplicative model; Multivariate ARMA model; Naive forecast; Neural networks; Noise; Non-linear estimation; Non-linear forecasting; Non-stationary; Normal distribution; Observation; Optimal parameter or weight value; Order selection criteria; Outlier; Parameter; Parsimony; Partial autocorrelation; Partial correlation; Pattern; Pegels' classification; Polynomial; Polynomial fitting; Post-sample evaluation; Prediction interval; Probability; Product life cycle; P-value; Qualitative or technological forecasting; Quantitative forecasting; R-squared; R-bar-squared; Randomness; Random sampling; Random walk; Regression; Regression coefficients; Regression with ARIMA errors; Regressor; Residual; Sample; Sampling distribution; Sampling error; S-curve; Seasonal adjustment; Seasonal data; Seasonal difference; Seasonal exponential smoothing; Seasonal index; Seasonal variation; Serial correlation; Significance; Simple regression; Slope; Smoothing; Specification error; Spectral analysis; Spencer's weighted moving average; Standard deviation; Standard error; Standardize; State space modeling; Stationary; Statistic; STL decomposition; Technological forecasting; Time series; Time series model; Tracking signal; Trading day; Transfer function; Transformation; Trend analysis; t-test; Turning point; Type of data; Unbiasedness; Updated forecast; Validation; Variance; Vector ARMA model; Weight; White noise; Winters exponential smoothing; X-11 decomposition; X-12-ARIMA decomposition.