Financial Stability
Financial Systems: The Anatomy of the Market Economy How the financial system is constructed, how it works, how to keep it fit and what good a bit of chocolate can do. Dossier In…
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Economic Failure and the Role of Plant Age and Size
Steffen Müller, Jens Stegmaier
Small Business Economics,
No. 3,
2015
Abstract
This paper introduces a large-scale administrative panel data set on corporate bankruptcy in Germany that allows for an econometric analysis of involuntary exits where previous studies mixed voluntary and involuntary exits. Approximately 83 % of all bankruptcies occur in plants with not more than 10 employees, and 61 % of all bankrupt plants are not older than 5 years. The descriptive statistics and regression analysis indicate substantial negative age dependence with respect to bankruptcy risk but confirm negative size dependence for mature plants only. Our results corroborate hypotheses stressing increasing capabilities and positional advantage, both predicting negative age dependence with respect to bankruptcy risk due to productivity improvements. The results are not consistent with the theories explaining age dependence via imprinting or structural inertia.
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Inflation Expectations: Does the Market Beat Professional Forecasts?
Makram El-Shagi
North American Journal of Economics and Finance,
No. 3,
2011
Abstract
The present paper compares expected inflation to (econometric) inflation forecasts based on a number of forecasting techniques from the literature using a panel of ten industrialized countries during the period of 1988 to 2007. To capture expected inflation, we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect.
The extracted unexpected inflation is compared to the forecasting errors of ten
econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which
are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.
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A Panel Data Analysis on China's Intra-Industry Trade in the Capital Goods Sector
Yiping Zhu
IWH Discussion Papers,
No. 18,
2009
Abstract
Diese Studie verwendet die Methode der Hausman-Taylor-2SLS Fehler-Komponenten zur Schätzung der Determinanten von Chinas Intraindustriellem
Handel (IIT) im Investitionsgütersektor mit seinen 26 Partnerländern. Sie disaggregiert IIT in horizontalen IIT (HIIT) und vertikalen IIT (VIIT). Investitionsgüter, Endprodukte und Halbfertigwaren werden separat geschätzt, um die Unterschiede des Handels zu interpretieren. Es zeigt sich, dass die wirtschaftliche Ähnlichkeit mit IIT-Halbfertigwaren signifikant negativ korreliert ist, aber bei IIT-Endprodukten keine Signifikanz besteht. Der Faktor Ausstattung weist keine Signifikanz bei der Bestimmung von IIT-Halbfertigwaren auf, obwohl er mit IIT-Endprodukten signifikant positiv korreliert ist. Wirtschaftsgröße ist sowohl mit IIT-Endprodukten als auch mit IIT-Halbfertigwaren signifikant negativ korreliert. Entfernung wirkt sich auf das Niveau von IIT-Endprodukten aus, hat aber einen geringeren Einfluss auf IIT-Halbfertigwaren. China hat im Bereich Halbfertigwaren relativ wenig intraindustriellen Handel mit ASEAN-Staaten. Da jedoch VIIT einen dominierenden Einfluss auf TIIT ausübt, bestehen keine bedeutenden Unterschiede zwischen den Schätzungsergebnissen von TIIT und VIIT.
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Inflation Expectations: Does the Market Beat Professional Forecasts?
Makram El-Shagi
IWH Discussion Papers,
No. 16,
2009
Abstract
The present paper compares expected inflation to (econometric) inflation forecasts
based on a number of forecasting techniques from the literature using a panel of
ten industrialized countries during the period of 1988 to 2007. To capture expected
inflation we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect.
The extracted unexpected inflation is compared to the forecasting errors of ten
econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which
are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.
Read article