An evaluation of Chinese macroeconomic forecasts

Abstract

This article evaluates the quality of professional macroeconomic forecasts in China for the years 1995-2009. Using a large panel of forecasts on four macroeconomic variables (GDP, inflation, consumption and investment), we reject the hypothesis of unbiasedness, and find that forecasters have been, on average, overly pessimistic. The source of the bias lies primarily in forecasters' slow adjustment to structural shocks to the level of economic growth. We also reject the hypothesis that forecasters use information efficiently, and find that a large number of forecasters overreact to economic news. Finally, we document large differences of forecast accuracy across both forecasters and variables.

New Methods of Evaluating the Forecasts Accuracy: A Case Study for USA Inflation

“…The authors also proposed a regression for comparing the predictions. Deschamps and Bianchi (2012) concluded that there are large differences between macroeconomic forecasts for China regarding the accuracy measures for consumption and investment, GDP and inflation. The slow adjustment to structural shocks generated biased predictions, the information being utilized relatively inefficient.…”

Analysis of forecasts of GDP growth and inflation for the Croatian economy

“…For instance, Chen, Costantini, and Deschamps (2016) analyse the accuracy of GDP growth and inflation forecasts in Asia, while Pierdzioch and R€ ulke (2015) focus on exchange rate forecasts in emerging economies in Asia, eastern Europe and South America. When it comes to single economy study, Tsuchiya and Suehara (2015) and Deschamps and Bianchi (2012) focus on China, Carvalho and Minella (2012) and Baghestani and Marchon (2015) deal with Brazil, Capistran and Lopez-Moctezuma (2014) investigate Mexican inflation and GDP growth forecasts, while Baghestani and Danila (2014) focus on inflation forecasting in the Czech Republic.…”

“…Although the above mentioned research sometimes differs in approaches and methods used, inflation and real growth rate of GDP dominate as macroeconomic variables analysed. Moreover, the three research papers that analyse both inflation and real GDP growth rates, Deschamps and Bianchi (2012), Capistran and Lopez-Moctezuma (2014) and Chen et al (2016) all use the three-dimensional panel of forecasts to test biasedness and efficiency. Forecast accuracy evaluation differs in approaches when it comes to directional accuracy testing with some researchers omitting this specific assessment such as Deschamps and Bianchi (2012) and Capistran and Lopez-Moctezuma (2014).…”

“…Moreover, the three research papers that analyse both inflation and real GDP growth rates, Deschamps and Bianchi (2012), Capistran and Lopez-Moctezuma (2014) and Chen et al (2016) all use the three-dimensional panel of forecasts to test biasedness and efficiency. Forecast accuracy evaluation differs in approaches when it comes to directional accuracy testing with some researchers omitting this specific assessment such as Deschamps and Bianchi (2012) and Capistran and Lopez-Moctezuma (2014). Research findings vary as they depend on the forecaster, variable, country, time horizon of the forecasts and even on the economic cycle according to Deschamps and Bianchi (2012) and IMF (2018).…”

“…Forecast accuracy evaluation differs in approaches when it comes to directional accuracy testing with some researchers omitting this specific assessment such as Deschamps and Bianchi (2012) and Capistran and Lopez-Moctezuma (2014). Research findings vary as they depend on the forecaster, variable, country, time horizon of the forecasts and even on the economic cycle according to Deschamps and Bianchi (2012) and IMF (2018). However, forecasts do seem to exhibit, as would be reasonable to expect, a general tendency of improving as forecast horizons become shorter.…”