Tracking Weekly State-Level Economic Conditions
Christiane Baumeister, Danilo Leiva-León, Eric Sims
Review of Economics and Statistics,
This paper develops a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We find considerable cross-state heterogeneity in the length, depth, and timing of business cycles. We illustrate the usefulness of these state-level indices for quantifying the main contributors to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of the Paycheck Protection Program. We also propose an aggregate indicator that gauges the overall weakness of the U.S. economy.
Switching to Good Policy? The Case of Central and Eastern European Inflation Targeters
The paper analyzes how actual monetary policy changed following the official adoption of inflation targeting in the Czech Republic, Hungary, and Poland and how it affected the volatilities of important macroeconomic variables in the years thereafter. To disentangle the effects of the policy shift from exogenous changes in the volatilities of these variables, a Markov-switching dynamic stochastic general equilibrium model is estimated that allows for regime switches in the policy parameters and the volatilities of shocks hitting the economies. Whereas estimation results reveal periods of high and low volatility for all three economies, the presence of different policy regimes is supported by the underlying data for the Czech Republic and Poland, only. In both economies, monetary policy switched from weak and unsystematic to strong and systematic responses to inflation dynamics. Simulation results suggest that the policy shifts of both central banks successfully reduced inflation volatility in the following years. The observed reduction in output volatility, on the other hand, is attributed more to a reduction in the size of external shocks.
Switching to Exchange Rate Flexibility? The Case of Central and Eastern European Inflation Targeters
FIW Working Paper,
This paper analyzes changes in the monetary policy in the Czech Republic, Hungary, and Poland following the policy shift from exchange rate targeting to inflation targeting around the turn of the millennium. Applying a Markovswitching dynamic stochastic general equilibrium model, switches in the policy parameters and the volatilities of shocks hitting the economies are estimated and quantified. Results indicate the presence of regimes of weak and strong responses of the central banks to exchange rate movements as well as periods of high and low volatility. Whereas all three economies switched to a less volatile regime over time, findings on changes in the policy parameters reveal a lower reaction to exchange rate movements in the Czech Republic and Poland, but an increased attention to it in Hungary. Simulations for the Czech Republic and Poland also suggest their respective central banks, rather than a sound macroeconomic environment, being accountable for reducing volatility in variables like inflation and output. In Hungary, their favorable developments can be attributed to a larger extent to the reduction in the size of external disturbances.
Forecasting Currency Crises: Which Methods signaled the South African Crisis of June 2006?
Tobias Knedlik, Rolf Scheufele
South African Journal of Economics,
In this paper we test the ability of three of the most popular methods to forecast South African currency crises with a special emphasis on their out-of-sample performance. We choose the latest crisis of June 2006 to conduct an out-of-sample experiment. The results show that the signals approach was not able to forecast the out-of-sample crisis correctly; the probit approach was able
to predict the crisis but only with models, that were based on raw data. The Markov-regime- switching approach predicts the out-of-sample crisis well. However, the results are not straightforward. In-sample, the probit models performed remarkably well and were also able to detect, at least to some extent, out-of-sample currency crises before their occurrence. The recommendation is to not restrict the forecasting to only one approach.
Three methods of forecasting currency crises: Which made the run in signaling the South African currency crisis of June 2006?
Tobias Knedlik, Rolf Scheufele
IWH Discussion Papers,
In this paper we test the ability of three of the most popular methods to forecast the South African currency crisis of June 2006. In particular we are interested in the out-ofsample performance of these methods. Thus, we choose the latest crisis to conduct an out-of-sample experiment. In sum, the signals approach was not able to forecast the outof- sample crisis of correctly; the probit approach was able to predict the crisis but just with models, that were based on raw data. Employing a Markov-regime-switching approach also allows to predict the out-of-sample crisis. The answer to the question of which method made the run in forecasting the June 2006 currency crisis is: the Markovswitching approach, since it called most of the pre-crisis periods correctly. However, the “victory” is not straightforward. In-sample, the probit models perform remarkably well and it is also able to detect, at least to some extent, out-of-sample currency crises before their occurrence. It can, therefore, not be recommended to focus on one approach only when evaluating the risk for currency crises.