Advances in Using Vector Autoregressions to Estimate Structural Magnitudes
Christiane Baumeister, James D. Hamilton
Econometric Theory,
forthcoming
Abstract
This paper surveys recent advances in drawing structural conclusions from vector autoregressions (VARs), providing a unified perspective on the role of prior knowledge. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns from both a frequentist and a Bayesian perspective about the way that results are typically reported for VARs that are set-identified using sign and other restrictions. We call attention to a common but previously unrecognized error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one only knows the effects of a single structural shock.
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Surges and Instability: The Maturity Shortening Channel
Xiang Li, Dan Su
Journal of International Economics,
forthcoming
Abstract
Capital inflow surges destabilize the economy through a maturity shortening mechanism. The underlying reason is that firms have incentives to redeem their debt on demand to accommodate the potential liquidity needs of global investors, which makes international borrowing endogenously fragile. Based on a theoretical model and empirical evidence at both the firm and macro levels, our main findings are twofold. First, a significant association exists between surges and shortened corporate debt maturity, especially for firms with foreign bank relationships and higher redeployability. Second, the probability of a crisis following surges with a flattened yield curve is significantly higher than that following surges without one. Our study suggests that debt maturity is the key to understand the financial instability consequences of capital inflow bonanzas.
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Forecasting Economic Activity Using a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to the
German GDP
Oliver Holtemöller, Boris Kozyrev
IWH Discussion Papers,
No. 6,
2024
Abstract
In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an autoregressive benchmark model in many practically relevant cases. Then, we applied GRNN to forecast quarterly German GDP growth by extending univariate GRNN to multivariate and mixed-frequency settings. We could distinguish between “normal” times and situations where the time-series behavior is very different from “normal” times such as during the COVID-19 recession and recovery. GRNN was superior in terms of root mean forecast errors compared to an autoregressive model and to more sophisticated approaches such as dynamic factor models if applied appropriately.
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Skill Mismatch and the Costs of Job Displacement
Frank Neffke, Ljubica Nedelkoska, Simon Wiederhold
Research Policy,
No. 2,
2024
Abstract
Establishment closures have lasting negative consequences for the workers displaced from their jobs. We study how these consequences vary with the amount of skill mismatch that workers experience after job displacement. Developing new measures of occupational skill redundancy and skill shortage, we analyze the work histories of individuals in Germany between 1975 and 2010. We estimate difference-in-differences models, using a sample of displaced workers who are matched to statistically similar non-displaced workers. We find that displacements increase the probability of occupation change eleven-fold. Moreover, the magnitude of post-displacement earnings losses strongly depends on the type of skill mismatch that workers experience in such job switches. Whereas skill shortages are associated with relatively quick returns to the earnings trajectories that displaced workers would have experienced absent displacement, skill redundancy sets displaced workers on paths with permanently lower earnings. We show that these differences can be attributed to differences in mismatch after displacement, and not to intrinsic differences between workers making different post-displacement career choices.
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Is Risk the Fuel of the Business Cycle? Financial Frictions and Oil Market Disturbances
Christoph Schult
IWH Discussion Papers,
No. 4,
2024
Abstract
I estimate a dynamic stochastic general equilibrium (DSGE) model for the United States that incorporates oil market shocks and risk shocks working through credit market frictions. The findings of this analysis indicate that risk shocks play a crucial role during the Great Recession and the Dot-Com bubble but not during other economic downturns. Credit market frictions do not amplify persistent oil market shocks. This result holds as long as entry and exit rates of entrepreneurs are independent of the business cycle.
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Trust, Politics and Post-IPO Performance: SOEs vs. the Private Sector
Bill Francis, Iftekhar Hasan, Xian Sun, Mingming Zhou
Economic and Political Studies,
forthcoming
Abstract
This paper empirically investigates the role of social trust in the long-term performance of the initial public offerings (IPOs) in China, controlling for the formal institutional environment. We find that privately owned or smaller IPO firms experience significantly better post-IPO performance when they are incorporated in regions with more social trust. The state-owned and bigger IPO firms, on the other hand, experience better long-term post-IPO performance when they are incorporated in regions with stronger formal institutions (e.g. court enforcement and contract holding). Political pluralism turns out to benefit all IPOs in the long term. In addition, our evidence shows that stronger social trust substitutes for the quality of court enforcement but complements the role of contract holding. These results are robust after controlling for alternative definitions of ownership, outliers, non-linear effects of institutions, and the potential endogeneity of institutions in the model.
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Tracking Weekly State-Level Economic Conditions
Christiane Baumeister, Danilo Leiva-León, Eric Sims
Review of Economics and Statistics,
forthcoming
Abstract
This paper develops a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We find considerable cross-state heterogeneity in the length, depth, and timing of business cycles. We illustrate the usefulness of these state-level indices for quantifying the main contributors to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of the Paycheck Protection Program. We also propose an aggregate indicator that gauges the overall weakness of the U.S. economy.
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12.01.2024 • 2/2024
Green transition and the debt brake: Implications of additional investment for public finances and private consumption in Germany
The German Climate Protection Act stipulates, among other things, that greenhouse gas emissions in Germany are to be reduced by 65% by 2030 compared to 1990 levels. The green investments required to achieve this target are likely to amount to around 2.5% of gross domestic product each year. According to the medium-term projection of the Halle Institute for Economic Research (IWH), the associated additional government spending on public investment and support measures cannot be financed from projected tax revenues. It is therefore to be expected that the tax burden on households will increase and private consumption will be curbed accordingly, if both the current form of the debt brake and the greenhouse gas reduction targets are maintained.
Oliver Holtemöller
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Financial Technologies and the Effectiveness of Monetary Policy Transmission
Iftekhar Hasan, Boreum Kwak, Xiang Li
European Economic Review,
January
2024
Abstract
This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with regional-level FinTech adoption. Results indicate that FinTech adoption generally mitigates the transmission of monetary policy to real GDP, consumer prices, bank loans, and housing prices, with the most significant impact observed in the weakened transmission to bank loan growth. The relaxed financial constraints, regulatory arbitrage, and intensified competition are the possible mechanisms underlying the mitigated transmission.
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A Congestion Theory of Unemployment Fluctuations
Yusuf Mercan, Benjamin Schoefer, Petr Sedláček
American Economic Journal: Macroeconomics,
No. 1,
2024
Abstract
We propose a theory of unemployment fluctuations in which newhires and incumbentworkers are imperfect substitutes. Hence, attempts to hire away the unemployed during recessions diminish the marginal product of new hires, discouraging job creation. This single feature achieves a ten-fold increase in the volatility of hiring in an otherwise standard search model, produces a realistic Beveridge curve despite countercyclical separations, and explains 30–40% of U.S. unemployment fluctuations. Additionally, it explains the excess procyclicality of new hires’ wages, the cyclical labor wedge, countercyclical earnings losses from job displacement, and the limited steady-state effects of unemployment insurance.
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