Media Reporting and Business Cycles: Empirical Evidence based on News Data

Recent literature suggests that news shocks could be an important driver of economic cycles. In this article, we use a direct measure of news sentiment derived from media reports. This allows us to examine whether innovations in the reporting tone correlate with changes in the assessment and expectations of the business situation as reported by firms in the German manufacturing sector. We fi nd that innovations in news reporting affect business expectations, even when conditioning on the current business situation and industrial production. The dynamics of the empirical model con rm theoretical predictions that news innovations affect real variables such as production via changes in expectations. Looking at individual sectors within manufacturing, we fi nd that macroeconomic news is at least as important for business expectations as sector-spefici c news. This is consistent with the existence of information complementarities across sectors

Golden Rule of Forecasting: Be Conservative

This article proposes a unifying theory, or the Golden Rule, or forecasting. The Golden Rule of Forecasting is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation. Twenty-eight guidelines are logically deduced from the Golden Rule. A review of evidence identified 105 papers with experimental comparisons; 102 support the guidelines. Ignoring a single guideline increased forecast error by more than two-fifths on average. Ignoring the Golden Rule is likely to harm accuracy most when the situation is uncertain and complex, and when bias is likely. Non-experts who use the Golden Rule can identify dubious forecasts quickly and inexpensively. To date, ignorance of research findings, bias, sophisticated statistical procedures, and the proliferation of big data, have led forecasters to violate the Golden Rule. As a result, despite major advances in evidence-based forecasting methods, forecasting practice in many fields has failed to improve over the past half-century