Information Feedback in Temporal Networks as a Predictor of Market Crashes
Stjepan Begušić, Zvonko Kostanjčar, Dejan Kovač, Boris Podobnik, H. Eugene Stanley
Complexity,
September
2018
Abstract
In complex systems, statistical dependencies between individual components are often considered one of the key mechanisms which drive the system dynamics observed on a macroscopic level. In this paper, we study cross-sectional time-lagged dependencies in financial markets, quantified by nonparametric measures from information theory, and estimate directed temporal dependency networks in financial markets. We examine the emergence of strongly connected feedback components in the estimated networks, and hypothesize that the existence of information feedback in financial networks induces strong spatiotemporal spillover effects and thus indicates systemic risk. We obtain empirical results by applying our methodology on stock market and real estate data, and demonstrate that the estimated networks exhibit strongly connected components around periods of high volatility in the markets. To further study this phenomenon, we construct a systemic risk indicator based on the proposed approach, and show that it can be used to predict future market distress. Results from both the stock market and real estate data suggest that our approach can be useful in obtaining early-warning signals for crashes in financial markets.
Read article
Early-Stage Business Formation: An Analysis of Applications for Employer Identification Numbers
Kimberly Bayard, Emin Dinlersoz, Timothy Dunne, John Haltiwanger, Javier Miranda, John Stevens
NBER Working Paper,
No. 24364,
2018
Abstract
This paper reports on the development and analysis of a newly constructed dataset on the early stages of business formation. The data are based on applications for Employer Identification Numbers (EINs) submitted in the United States, known as IRS Form SS-4 filings. The goal of the research is to develop high-frequency indicators of business formation at the national, state, and local levels. The analysis indicates that EIN applications provide forward-looking and very timely information on business formation. The signal of business formation provided by counts of applications is improved by using the characteristics of the applications to model the likelihood that applicants become employer businesses. The results also suggest that EIN applications are related to economic activity at the local level. For example, application activity is higher in counties that experienced higher employment growth since the end of the Great Recession, and application counts grew more rapidly in counties engaged in shale oil and gas extraction. Finally, the paper provides a description of new public-use dataset, the “Business Formation Statistics (BFS),” that contains new data series on business applications and formation. The initial release of the BFS shows that the number of business applications in the 3rd quarter of 2017 that have relatively high likelihood of becoming job creators is still far below pre-Great Recession levels.
Read article
The Appropriateness of the Macroeconomic Imbalance Procedure for Central and Eastern European Countries
Martina Kämpfe, Tobias Knedlik
IWH Discussion Papers,
No. 16,
2017
Abstract
The experience of Central and Eastern European countries (CEEC) during the global financial crisis and in the resulting European debt crises has been largely different from that of other European countries. This paper looks at the specifics of the CEEC in recent history and focuses in particular on the appropriateness of the Macroeconomic Imbalances Procedure for this group of countries. In doing so, the macroeconomic situation in the CEEC is highlighted and macroeconomic problems faced by these countries are extracted. The findings are compared to the results of the Macroeconomic Imbalances Procedure of the European Commission. It is shown that while the Macroeconomic Imbalances Procedure correctly identifies some of the problems, it understates or overstates other problems. This is due to the specific construction of the broadened surveillance procedure, which largely disregarded the specifics of catching-up economies.
Read article
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 expost 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. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. 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.
Read article
09.06.2016 • 22/2016
The German Economy Benefits from Strong Domestic Demand
In 2016, the moderate upswing of the German economy continues. Incomes grow due to the steady expansion in employment, and the fall in energy prices has propped up the purchasing power of private households. As a consequence, private consumption expands healthily; investment in housing is additionally stimulated by very low interest rates. Exports, however, expand only moderately, as the world economy is rather weak. All in all, the IWH forecasts the German GDP to expand by 1.8% in this year and by 1.6% in 2017.
Oliver Holtemöller
Read press release
Taking the First Step - What Determines German Laser Source Manufacturers' Entry into Innovation Networks?
Jutta Günther, Muhamed Kudic, Andreas Pyka
International Journal of Innovation Management,
No. 5,
2015
Abstract
Early access to technological knowledge embodied in the industry’s innovation network can provide an important competitive advantage to firms. While the literature provides much evidence on the positive effects of innovation networks on firms’ performance, not much is known about the determinants of firms’ initial entry into such networks. We analyze firms’ timing and propensity to enter the industry’s innovation network. More precisely, we seek to shed some light on the factors affecting the duration between firm founding and its first cooperation event. In doing so, we apply a unique longitudinal event history dataset based on the full population of German laser source manufacturers. Innovation network data stem from official databases providing detailed information on the organizations involved, subject of joint research and development (R&D) efforts as well as start and end times for all publically funded R&D projects between 1990 and 2010. Estimation results from a non-parametric event history model indicate that micro firms enter the network later than small-sized or large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of geographical determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.
Read article
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.
Read article
Do We Need New Modelling Approaches in Macroeconomics?
Claudia M. Buch, Oliver Holtemöller
Financial Cycles and the Real Economy: Lessons for CESEE Countries,
2014
Abstract
The economic and financial crisis that emerged in 2008 also initiated an intense discussion on macroeconomic research and the role of economists in society. The debate focuses on three main issues. Firstly, it is argued that economists failed to predict the crisis and to design early warning systems. Secondly, it is claimed that economists use models of the macroeconomy which fail to integrate financial markets and which are inadequate to model large economic crises. Thirdly, the issue has been raised that economists invoke unrealistic assumptions concerning human behaviour by assuming that all agents are self-centred, rationally optimizing individuals. In this paper, we focus on the first two issues. Overall, our thrust is that the above statements are a caricature of modern economic theory and empirics. A rich field of research developed already before the crisis and picked up shortcomings of previous models.
Read article
Do We Need New Modelling Approaches in Macroeconomics?
Claudia M. Buch, Oliver Holtemöller
IWH Discussion Papers,
No. 8,
2014
Abstract
The economic and financial crisis that emerged in 2008 also initiated an intense discussion on macroeconomic research and the role of economists in society. The debate focuses on three main issues. Firstly, it is argued that economists failed to predict the crisis and to design early warning systems. Secondly, it is claimed that economists use models of the macroeconomy which fail to integrate financial markets and which are inadequate to model large economic crises. Thirdly, the issue has been raised that economists invoke unrealistic assumptions concerning human behaviour by assuming that all agents are self-centred, rationally optimizing individuals. In this paper, we focus on the first two issues. Overall, our thrust is that the above statements are a caricature of modern economic theory and empirics. A rich field of research developed already before the crisis and picked up shortcomings of previous models.
Read article
The Impact of Preferences on Early Warning Systems - The Case of the European Commission's Scoreboard
Tobias Knedlik
European Journal of Political Economy,
2014
Abstract
The European Commission’s Scoreboard of Macroeconomic Imbalances is a rare case of a publicly released early warning system. It allows the preferences of the politicians involved to be analysed with regard to the two potential errors of an early warning system – missing a crisis and issuing a false alarm. These preferences might differ with the institutional setting. Such an analysis is done for the first time in this article for early warning systems in general by using a standard signals approach, including a preference-based optimisation approach, to set thresholds. It is shown that, in general, the thresholds of the Commission’s Scoreboard are set low (resulting in more alarm signals), as compared to a neutral stand. Based on political economy considerations the result could have been expected.
Read article
