The Joint Dynamics of Sovereign Ratings and Government Bond Yields
Makram El-Shagi, Gregor von Schweinitz
Abstract
In the present paper, we build a bivariate semiparametric dynamic panel model to repro-duce the joint dynamics of sovereign ratings and government bond yields. While the individual equations resemble Pesaran-type cointegration models, we allow for different long-run relationships in both equations, nonlinearities in the level effect of ratings, and asymmetric effects in changes of ratings and yields. We find that the interest rate equation and the rating equation imply significantly different long-run relationships. While the high persistence in both interest rates and ratings might lead to the misconception that they follow a unit root process, the joint analysis reveals that they converge slowly to a joint equilibrium. While this indicates that there is no vicious cycle driving countries into default, the persistence of ratings is high enough that a rating shock can have substantial costs. Generally, the interest rate adjusts rather quickly to the risk premium that is in line with the rating. For most ratings, this risk premium is only marginal. However, it becomes substantial when ratings are downgraded to highly speculative (a rating of B) or lower. Rating shocks that drive the rating below this threshold can increase the interest rate sharply, and for a long time. Yet, simulation studies based on our estimations show that it is highly improbable that rating agencies can be made responsible for the most dramatic spikes in interest rates.
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The Quantity Theory Revisited: A New Structural Approach
Makram El-Shagi, Sebastian Giesen
Macroeconomic Dynamics,
No. 1,
2015
Abstract
We propose a unified identification scheme to identify monetary shocks and track their propagation through the economy. We combine three approaches dealing with the consequences of monetary shocks. First, we adjust a state space version of the P-star type model employing money overhang as the driving force of inflation. Second, we identify the contemporaneous impact of monetary policy shocks by applying a sign restriction identification scheme to the reduced form given by the state space signal equations. Third, to ensure that our results are not distorted by the measurement error exhibited by the official monetary data, we employ the Divisia M4 monetary aggregate provided by the Center for Financial Stability. Our approach overcomes one of the major difficulties of previous models by using a data-driven identification of equilibrium velocity. Thus, we are able to show that a P-star model can fit U.S. data and money did indeed matter in the United States.
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The Social Capital Legacy of Communism-results from the Berlin Wall Experiment
Peter Bönisch, Lutz Schneider
European Journal of Political Economy,
No. 32,
2013
Abstract
In this paper we establish a direct link between the communist history, the resulting structure of social capital, and attitudes toward spatial mobility. We argue that the communist regime induced a specific social capital mix that discouraged geographic mobility even after its demise. Theoretically, we integrate two branches of the social capital literature into one more comprehensive framework distinguishing an open type and a closed type of social capital. Using the German Socio-Economic Panel (GSOEP) we take advantage of the natural experiment that separated Germany into two parts after the WWII to identify the causal effect of social capital on mobility. We estimate a three equation ordered probit model and provide strong empirical evidence for our theoretical propositions.
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Geoadditive Models for Regional Count Data: An Application to Industrial Location
Davide Castellani
ERSA conference papers,
2012
Abstract
We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data which allows us to simultaneously address some important methodological issues, such as spatial clustering, nonlinearities and overdispersion. We apply this model to study location determinants of inward greenfield investments occurred over the 2003-2007 period in 249 European regions. The inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity which induces spatial clustering. Allowing for nonlinearities reveals, in line with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some limit value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs would never overcome positive agglomeration externalities.
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The GVAR Handbook: Structure and Applications of a Macro Model of the Global Economy for Policy Analysis
Filippo di Mauro, M. Hashem Pesaran
Oxford University Press,
2013
Abstract
The recent crisis has shown yet again how the world economies are globally interlinked, via a complex net of transmission channels. When it comes, however, to build econometric frameworks aimed at analysing such linkages, modellers are faced with what is called the "curse of dimensionality": there far too many parameters to be estimated with respect to the available observations. The GVAR, a VAR based model of the global economy, offers a solution to this problem. The basic model is composed of a large number of country specific models, comprising domestic, foreign and purely global variables. The foreign variables, however, are treated as weakly exogenous. This assumption, which is typically held when empirically tested for virtually all economies - with the notable exception of the US which is treated differently - allows to estimate first the individual country models separately. Only in a second stage country-specific models are simultaneously solved, thus allowing global interactions.This volume presents - for a first time in a compact and rather easy to read format - principles and structure of the basic GVAR model and a number of its many applications and extensions developed in the last few years by a growing literature. Its main objective is to show how powerful the model can be as a tool for forecasting and scenario analysis. The clear modelling structure of the GVAR appeals to policy makers and practitioners as shown by its growing use among major institutions, as well as by econometricians, as shown by the main extensions and applications.
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Natural-resource or Market-seeking FDI in Russia? An Empirical Study of Locational Factors Affecting the Regional Distribution of FDI Entries
K. Gonchar, Philipp Marek
IWH Discussion Papers,
No. 3,
2013
Abstract
This paper conducts an empirical study of the factors that affect the spatial distribution of foreign direct investment (FDI) across regions in Russia; in particular, this paper is concerned with those regions that are endowed with natural resources and market-related benefits. Our analysis employs data on Russian firms with a foreign investor during the 2000-2009 period and linked regional statistics in the conditional logit model. The main findings are threefold. First, we conclude that one theory alone is not able to explain the geographical pattern of foreign investments in Russia. A combination of determinants is at work; market-related factors and the availability of natural resources are important factors in attracting FDI. The relative importance of natural resources seems to grow over time, despite shocks associated with events such as the Yukos trial. Second, existing agglomeration economies encourage foreign investors by means of forces generated simultaneously by sector-specific and inter-sectoral externalities. Third, the findings imply that service-oriented FDI co-locates with extraction industries in resource-endowed regions. The results are robust when Moscow is excluded and for subsamples including only Greenfield investments or both Greenfield investments and mergers and acquisitions (M&A).
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The Tradeoff Between Redistribution and Effort: Evidence from the Field and from the Lab
Claudia M. Buch, C. Engel
Max Planck Institute for Research on Collective Goods Working Paper,
No. 10,
2012
Abstract
We use survey and experimental data to explore how effort choices and preferences for redistribution are linked. Under standard preferences, redistribution would reduce effort. This is different with social preferences. Using data from the World Value Survey, we find that respondents with stronger preferences for redistribution tend to have weaker incentives to engage in effort, but that the reverse does not hold true. Using a lab experiment, we show that redistribution choices even increase in imposed effort. Those with higher ability are willing to help the needy if earning income becomes more difficult for everybody.
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The Halle Economic Projection Model
Sebastian Giesen, Oliver Holtemöller, Juliane Scharff, Rolf Scheufele
Economic Modelling,
No. 4,
2012
Abstract
In this paper we develop an open economy model explaining the joint determination of output, inflation, interest rates, unemployment and the exchange rate in a multi-country framework. Our model -- the Halle Economic Projection Model (HEPM) -- is closely related to studies published by Carabenciov et al. Our main contribution is that we model the Euro area countries separately. In doing so, we consider Germany, France, and Italy which represent together about 70 percent of Euro area GDP. The model combines core equations of the New-Keynesian standard DSGE model with empirically useful ad-hoc equations. We estimate this model using Bayesian techniques and evaluate the forecasting properties. Additionally, we provide an impulse response analysis and a historical shock decomposition.
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An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models
Makram El-Shagi
International Economics and Economic Policy,
No. 4,
2011
Abstract
We develop an evolutionary algorithm to estimate Threshold Vector Error Correction models (TVECM) with more than two cointegrated variables. Since disregarding a threshold in cointegration models renders standard approaches to the estimation of the cointegration vectors inefficient, TVECM necessitate a simultaneous estimation of the cointegration vector(s) and the threshold. As far as two cointegrated variables are considered, this is commonly achieved by a grid search. However, grid search quickly becomes computationally unfeasible if more than two variables are cointegrated. Therefore, the likelihood function has to be maximized using heuristic approaches. Depending on the precise problem structure the evolutionary approach developed in the present paper for this purpose saves 90 to 99 per cent of the computation time of a grid search.
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Modelling Country Default Risk as a Latent Variable: A Multiple Indicators Multiple Causes Approach
A. Bühn, Stefan Eichler, Dominik Maltritz
Applied Economics,
No. 36,
2012
Abstract
We study the determinants of country default risk by applying a Multiple Indicators Multiple Causes (MIMIC) model. This accounts for the fact that country default risk is an unobservable variable. Whereas existing (regression-based) approaches typically use only one of several possible country default risk indicators as the dependent variable, the MIMIC model enables us to consider several indicators at once. The simultaneous consideration of sovereign yield spreads and Standard and Poor (S&P) ratings may help to improve the identification of the latent country default risk. Our results confirm most of the literature's main findings regarding important determinants of country default risk, refute others and provide new evidence to controversial questions.
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