Fiscal Spending Multiplier Calculations based on Input-Output Tables – with an Application to EU Members
Toralf Pusch, A. Rannberg
Abstract
Fiscal spending multiplier calculations have been revived in the aftermath of the
global financial crisis. Much of the current literature is based on VAR estimation
methods and DSGE models. The aim of this paper is not a further deepening of
this literature but rather to implement a calculation method of multipliers which is
suitable for open economies like EU member states. To this end, Input-Output tables are used as by this means the import intake of domestic demand components can be isolated in order to get an appropriate base for the calculation of the relevant import quotas. The difference of this method is substantial – on average the calculated multipliers are 15% higher than the conventional GDP fiscal spending multiplier for EU members. Multipliers for specific spending categories are comparably high, ranging between 1.4 and 1.8 for many members of the EU. GDP drops due to budget consolidation might therefore be substantial if monetary policy is not able to react in an expansionary manner.
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Preventing Innovative Cooperations: The Legal Exemptions Unintended Side Effect
Christian Growitsch, Nicole Nulsch, Margarethe Rammerstorfer
European Journal of Law and Economics,
No. 1,
2012
Abstract
In 2004, European competition law had been considerable changed by the introduction of the new Council Regulation No. 1/2003. One of the major renewals was the replacement of the centralized notification system for inter-company cooperations in favor of a so-called legal exemption system. We analyze the implications of this reform and its arising uncertainty on the agreements firms implement, especially on innovative agreements like vertical R&D agreements. By means of a decision theoretic approach, we show that the law’s intention to reduce the incentive to establish illegal cartels will be reached but innovating cooperations might be prevented. To avoid this unintended side effect, fines but not the monitoring activities should be increased.
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Business Volatility, Job Destruction, and Unemployment
Steven J. Davis, R. Jason Faberman, John Haltiwanger, Ron S. Jarmin, Javier Miranda
American Economic Journal: Macroeconomics,
No. 2,
2010
Abstract
Unemployment inflows fell from 4 percent of employment per month in the early 1980s to 2 percent by the mid 1990s. Using low frequency movements in industry-level data, we estimate that a 1 percentage point drop in the quarterly job destruction rate lowers the monthly unemployment inflow rate by 0.28 points. By our estimates, declines in job destruction intensity account for 28 (55) percent of the fall in unemployment inflows from 1982 (1990) to 2005. Slower job destruction accounts for similar fractions of long-term declines in the rate of unemployment.
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Differences in Labor Supply to Monopsonistic Firms and the Gender Pay Gap: An Empirical Analysis Using Linked Employer‐Employee Data from Germany
Boris Hirsch, Thorsten Schank, Claus Schnabel
Journal of Labor Economics,
No. 2,
2010
Abstract
This article investigates women’s and men’s labor supply to the firm within a semistructural approach based on a dynamic model of new monopsony. Using methods of survival analysis and a large linked employer‐employee data set for Germany, we find that labor supply elasticities are small (1.9–3.7) and that women’s labor supply to the firm is less elastic than men’s (which is the reverse of gender differences in labor supply usually found at the level of the market). Our results imply that at least one‐third of the gender pay gap might be wage discrimination by profit‐maximizing monopsonistic employers.
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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.
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