Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009

In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact that they form a class of universal approximators and may be expected to work well during exceptional periods such as major economic crises. Neural network models are often difficult to estimate, and we follow the idea of White (2006) of transforming the specification and nonlinear estimation problem into a linear model selection and estimation problem. To this end, we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge Estimator, which is better known to statisticians. The performances of these three model selectors are compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series from the G7 countries and the four Scandinavian ones, and focus on forecasting during the economic crisis 2007–2009. The forecast accuracy is measured using the root mean square forecast error. Hypothesis testing is also used to compare the performances of the different techniques.     

我们俩

中国与欧盟在政治、经济、文化诸方面的深度合作无需多言,作为欧盟派驻在华的工作人员,我们衷心希望,中欧海关合作能够“更上层楼”。     

Strukturelle Finanzierungssalden auf verlässliche Füße stellen

Wirtschaftsdienst - Derzeit wird in der EU und Deutschland diskutiert, wie die Fiskalregeln zukünftig ausgestaltet sein sollen. Ein Punkt ist dabei die Berechnung des strukturellen...     

Smoothing and Benchmarking for Small Area Estimation

Small area estimation is concerned with methodology for estimating population parameters associated with a geographic area defined by a cross-classification that may also include non-geographic dimensions. In this paper, we develop constrained estimation methods for small area problems: those requiring smoothness with respect to similarity across areas, such as geographic proximity or clustering by covariates, and benchmarking constraints, requiring weighted means of estimates to agree across levels of aggregation. We develop methods for constrained estimation decision theoretically and discuss their geometric interpretation. The constrained estimators are the solutions to tractable optimisation problems and have closed-form solutions. Mean squared errors of the constrained estimators are calculated via bootstrapping. Our approach assumes the Bayes estimator exists and is applicable to any proposed model. In addition, we give special cases of our techniques under certain distributional assumptions. We illustrate the proposed methodology using web-scraped data on Berlin rents aggregated over areas to ensure privacy.     

Formation of firms' production decisions in finnish manufacturing industries

Business survey data have recently been used in several studies to shed light on the formation of firms' plans and expectations. The main tool for analysis has been the multivariate conditional log-linear model. The trichotomous answers in a typical business survey have an ordering. This makes it possible to analyse firms' production decisions with a categorized version of Cox's proportional hazards model. In this paper the production decisions of Finnish firms are investigated using data from the Finnish business survey. The results obtained are largely in accord with the implications of the production smoothing model of Blinder (1982).     

National Culture and Takeover Contest Outcomes

We examine the effects of cultural differences on the outcome of takeover contests. Our main focus is on individuality, which we posit to have an effect on firm behavior in international takeover contests. In a sample of international acquisitions with bidders from multiple countries, we find that individuality positively relates to the probability of placing the winning bid. We further find that takeover contest winners with high individuality scores experience lower announcement returns. Our results are consistent with the literature that links individuality to overconfidence. Our evidence suggests that firms should control culture‐related behavioral biases in their mergers and acquisitions activity.     

Empirical Risk Analysis of Pension Insurance: The Case of Germany

The book reserve system is the most widespread method of financing occupational pension plans in Germany. The pension liabilities are mutually insured by the Pensions-Sicherungs-Verein VVaG (PSVaG) against bankruptcy. The PSVaG recently stated that the insurance system needed to be reformed. In the future, risk-adjusted premiums as foreseen for the newly established Pension Protection Fund in the United Kingdom could become feasible. We perform a credit portfolio analysis to determine the risk profile of the PSVaG. The magnitude of a tail risk event suggests that under the current financing system it can only be smoothed out over decades. Under an expected loss pricing plan insurance premiums would vary greatly. In a marginal risk contribution approach the variation of the premiums would be less pronounced.