Combination forecasts of output growth in a seven-country data set

By James H. Stock, Mark W. Watson. 2004

1,175 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/4bd80e5ed3365130bf6feef6028ea65edbe52f86

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In Management Science and Operations Research

Citations in the corpus

Forecasting with Panel Data (2008, methodology): “This predictor was considered by Wansbeek and Kapteyn (1978), Lee and Gri¢ ths (1979) and Taub (1979). The BLUP are optimal assuming true values of the variance components.”
Persistence in forecasting performance and conditional combination strategies (2006, methodology): “9These values are higher than the values (0.25, 0.5 and 1) considered by Stock and Watson (2004).”
Macroeconomic forecast accuracy in a data‐rich environment (2019, background): “Here, we follow Stock and Watson (2004) and define the discounted weight on the ith forecast as follows wit = m−1it∑M j=1m −1 jt , where mit is the discounted MSPE for the forecast i: mit = t−h∑ s=T0 ρt−h−s(ys+h − y(h,i)s+h|s) 2, and ρ is a discount factor.”
Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version (2013, positive): “Stock and Watson (1999, 2004, 2012) provide detailed empirical evidence demonstrating the gains of forecast combination.”
Combination of long term and short term forecasts, with application to tourism demand forecasting (2011, background): “Another approach, proposed by Stock and Watson (2004) is based on shrinking the weights linearly toward the equal weight solution.”
Electricity price forecasting: A review of the state-of-the-art with a look into the future (2014, background): “the arithmetic mean of individual forecasts) stands out as the most popular and surprisingly robust approach (Bunn, 1985b; Clemen, 1989; Genre et al., 2013; Stock and Watson, 2004).”
Averaging estimators for autoregressions with a near unit root (2010, background): “When p = 1 then T0c = (1− c)Wc(1) and f0(c, 1) = (1− c)2 ( exp (2c)− 1 2c ) .”
Predictability of Currency Carry Trades and Asset Pricing Implications (2013, positive): “Guided by Stock and Watson (2004), our next tests involve combination forecasts, which are weighted averages of individual predictions, and arguably perform better than the components.”
Model Averaging and Its Use in Economics (2017, background): “Stock and Watson (2004) examine a number of weighting schemes in terms of the accuracy of point forecasts and find that forecast combinations can perform well in comparison with single models, but that the best weighting schemes are often the ones that incorporate little or no data adaptivity.”
Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models (2019, methodology): “Therefore, with reference to the multivariate combined forecast concept of Timmermann, we use the weighting schemes proposed by Stock and Watson (2004, 2008) and Andreou et al. (2013) to combine several models with high forecast accuracy.”