The U.S. Business Cycle, 1867–2006: A Dynamic Factor Approach

Currency Versus Banking in the Financial Crisis of 1931

“…We also notice a very good fit with a broadly based factor of economic activity calculated in Ritschl et al. (). Results once again confirm the observation by Stock and Watson () that one‐factor models describe the real state of the economy quite well.…”

Irish GDP between the Famine and the First World War: estimates based on a dynamic factor model

“…Dynamic factor models have been used previously in the estimation of business cycle fluctuations in both contemporary (Stock and Watson 1989) and historical (Sarferaz and Uebele 2009;Ritschl et al 2016) contexts. The basic idea is that a time series is likely to be influenced by one or potentially more common factors as well as an idiosyncratic component.…”

“…Hickson and Turner (2008) argue, "as stock-market performance is widely regarded as a bellwether for real economic activity, our indices can serve as a measure of the levels and fluctuations of real economic activity in Ireland during an important period in its economic development." A measure of equity prices was also used in Ritschl et al (2016). The benchmark estimates used in step 6 for every tenth year between 1861 and 1911 are calculated as follows.…”

“…This paper proposes a solution to the standstill, which can be applied in other contexts in economic history for which similar conditions prevail. Building on the business cycle literature that identifies the cycle using factors models (Sarferaz and Uebele 2009;Ritschl et al 2016), we develop a two-stage approach to estimate GDP. In the first stage, a dynamic factor model is estimated to identify the common movement in a set of key macroeconomic variables.…”

Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother

“…They have therefore become popular among macroeconometricians; see, e.g., Breitung and Eickmeier (2006), for an overview. Areas of economic analysis using dynamic factor models include, for example, yield curve modeling (e.g., Diebold and Li 2006;, financial risk-return analysis (Ludvigson and Ng 2007), monetary policy analysis (e.g., Bernanke et al 2005;Boivin et al 2009), business cycle analysis (e.g., Forni and Reichlin 1998;Eickmeier 2007;Ritschl et al 2016), forecasting (e.g., Stock and Watson 2002a, b) and nowcasting the state of the economy, that is, forecasting of the very recent past, the present, or the very near future of indicators for economic activity, such as the gross domestic product (GDP) (see, e.g., Banbura et al 2012, and references therein). Information of the economic activity is of great importance for decision makers in, for instance, governments, central banks and financial markets.…”