Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics,
No. 1,
2020
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Why is Unemployment so Countercyclical?
Lawrence J. Christiano, Martin S. Eichenbaum, Mathias Trabandt
Abstract
We argue that wage inertia plays a pivotal role in allowing empirically plausible variants of the standard search and matching model to account for the large countercyclical response of unemployment to shocks.
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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Total Factor Productivity and the Terms of Trade
Jan Teresinski
IWH-CompNet Discussion Papers,
No. 6,
2019
Abstract
In this paper we analyse how the terms of trade (TOT) – the ratio of export prices to import prices – affect total factor productivity (TFP). We provide empirical macroeconomic evidence for the European Union countries based on the times series SVAR analysis and microeconomic evidence based on industry level data from the Competitiveness Research Network (CompNet) database which shows that the terms of trade improvements are associated with a slowdown in the total factor productivity growth. Next, we build a theoretical model which combines open economy framework with the endogenous growth theory. In the model the terms of trade improvements increase demand for labour employed in exportable goods production at the expense of technology production (research and development – R&D) which leads to a shift of resources from knowledge development towards physical exportable goods. This reallocation has a negative impact on the TFP growth. Under a plausible calibration the model is able to replicate the observed empirical pattern.
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Resolving the Missing Deflation Puzzle
Jesper Lindé, Mathias Trabandt
Abstract
We propose a resolution of the missing deflation puzzle. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.
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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Historical Social Research,
Special Issue: Governing by Numbers
2019
Abstract
In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.
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Should We Use Linearized Models To Calculate Fiscal Multipliers?
Jesper Lindé, Mathias Trabandt
Journal of Applied Econometrics,
No. 7,
2018
Abstract
We calculate the magnitude of the government consumption multiplier in linearized and nonlinear solutions of a New Keynesian model at the zero lower bound. Importantly, the model is amended with real rigidities to simultaneously account for the macroeconomic evidence of a low Phillips curve slope and the microeconomic evidence of frequent price changes. We show that the nonlinear solution is associated with a much smaller multiplier than the linearized solution in long‐lived liquidity traps, and pin down the key features in the model which account for the difference. Our results caution against the common practice of using linearized models to calculate fiscal multipliers in long‐lived liquidity traps.
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Inference in Structural Vector Autoregressions when the Identifying Assumptions are not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations
Christiane Baumeister, James D. Hamilton
Journal of Monetary Economics,
2018
Abstract
Point estimates and error bands for SVARs that are set identified are only justified if the researcher is persuaded that some parameter values are a priori more plausible than others. When such prior information exists, traditional approaches can be generalized to allow for doubts about the identifying assumptions. We use information about both structural coefficients and impacts of shocks and propose a new asymmetric t-distribution for incorporating information about signs in a nondogmatic way. We apply these methods to a three-variable macroeconomic model and conclude that monetary policy shocks are not the major driver of output, inflation, or interest rates.
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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Abstract
In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.
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On DSGE Models
Lawrence J. Christiano, Martin S. Eichenbaum, Mathias Trabandt
Journal of Economic Perspectives,
No. 3,
2018
Abstract
The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.
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