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November  
15:00 - 16:00 // Paper in progress presentation

Title: Nonlinearity in Labour Share Forecasting – Intersectoral Approach
 
Author: Stanislav Rogachev, 2nd-year PHD student, HSE St.Petersburg
Area of Scientific Interests: Labour Economics, Econometrics

Abstract
We forecast labour share for 18 KLEMS-classified economic sectors, 12 European countries. The choice is driven by data availability. For each sector, 11 specifications of time component in CES production function with factor augmenting technical change are tested. This includes comparing models with linear, nonlinear time and the same with structural breaks. Then, three degrees of models ‘power’ are proposed to characterize whether a model is consistent and valid for prediction. Here, residuals stationarity and autocorrelation are investigated as well as regressors and structural breaks statistical significance. Finally, 3D cube is visualized (dimensions: country-sector-model) to outline predictive power of models valid for forecasting.
To sum up main results, models with structural break in nonlinear time component show better predictive power according to the derived criteria. Next, overall labour share decline cannot be stated as only 7 sectors out of 18 have decreasing trend in more than one third of cases (countries). Additionally, each country sectors are grouped by LS forecast average value into four interval categories. The modal values of these intervals are derived to obtain general understanding of average future value for a certain sector. The last but not the least, forecasts with identical LS trends were combined for the purpose of generalizing.