Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
Abstract
Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The ex-post threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Journal of International Money and Finance,
No. 35,
2013
Abstract
The signals approach as an early-warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it cannot distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful results; (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach; and (3) that indicators which are found to be significant in-sample usually perform similarly well out-of-sample.
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Technological Intensity of Government Demand and Innovation
Viktor Slavtchev, Simon Wiederhold
Abstract
Governments purchase everything from airplanes to zucchini. This paper investigates whether the technological intensity of government demand affects corporate R&D activities. In a quality-ladder model of endogenous growth, we show that an increase in the share of government purchases in high-tech industries increases the rewards for innovation, and stimulates private-sector R&D at the aggregate level. We test this prediction using administrative data on federal procurement performed in US states. Both panel fixed effects and instrumental variable estimations provide results in line with the model. Our findings bring public procurement within the realm of the innovation policy debate.
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Does Central Bank Staff Beat Private Forecasters?
Makram El-Shagi, Sebastian Giesen, A. Jung
IWH Discussion Papers,
No. 5,
2012
Abstract
In the tradition of Romer and Romer (2000), this paper compares staff forecasts of the Federal Reserve (Fed) and the European Central Bank (ECB) for inflation and output with corresponding private forecasts. Standard tests show that the Fed and less so the ECB have a considerable information advantage about inflation and output. Using novel tests for conditional predictive ability and forecast stability for the US, we identify the driving forces of the narrowing of the information advantage of Greenbook forecasts coinciding with the Great Moderation.
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Forecasting Currency Crises: Which Methods signaled the South African Crisis of June 2006?
Tobias Knedlik, Rolf Scheufele
South African Journal of Economics,
2008
Abstract
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.
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Deeper, Wider and More Competitive? Monetary Integration, Eastern Enlargement and Competitiveness in the European Union
Gianmarco Ottaviano, Daria Taglioni, Filippo di Mauro
ECB Working Paper,
No. 847,
2008
Abstract
What determines a country’s ability to compete in international markets? What fosters the global competitiveness of its firms? And in the European context, have key elements of the EU strategy such as EMU and enlargement helped or hindered domestic firms’ competitiveness in local and global markets? We address these questions by calibrating and simulating a conceptual framework that, based on Melitz and Ottaviano (2005), predicts that tougher and more transparent international competition forces less productive firms out the market, thereby increasing average productivity as well as reducing average prices and mark-ups. The model also predicts a parallel reduction of price dispersion within sectors. Our conceptual framework allows us to disentangle the effects of technology and freeness of entry from those of accessibility. On the one hand, by controlling for the impact of trade frictions, we are able to construct an index of ‘revealed competitiveness’, which would drive the relative performance of countries in an ideal world in which all faced the same barriers to international transactions. On the other hand, by focusing on the role of accessibility while keeping ‘revealed competitiveness’ as given, we are able to evaluate the impacts of EMU and enlargement on the competitiveness of European firms. We find that EMU positively affects the competitiveness of firms located in participating economies. Enlargement has, instead, two contrasting effects. It improves the accessibility of EU members but it also increases substantially the relative importance of unproductive competitors from Eastern Europe. JEL Classification: F12, R13.
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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,
No. 17,
2007
Abstract
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.
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