The European Refugee Crisis and the Natural Rate of Output
Katja Heinisch, Klaus Wohlrabe
Abstract
The European Commission follows a harmonized approach for calculating structural (potential) output for EU member states that takes into account labor as an important ingredient. This paper shows how the recent huge migrants inflow to Europe affects trend output. Due to the fact that the immigrants immediately increase the working population but effectively do not enter the labor market, we illustrate that the potential output is potentially upward biased without any corrections. Taking Germany as an example, we find that the average medium-term potential growth rate is lower if the migration flow is modeled adequately compared to results based on the unadjusted European Commission procedure.
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Global Food Prices and Monetary Policy in an Emerging Market Economy: The Case of India
Oliver Holtemöller, Sushanta Mallick
Journal of Asian Economics,
2016
Abstract
This paper investigates a perception in the political debates as to what extent poor countries are affected by price movements in the global commodity markets. To test this perception, we use the case of India to establish in a standard SVAR model that global food prices influence aggregate prices and food prices in India. To further analyze these empirical results, we specify a small open economy New-Keynesian model including oil and food prices and estimate it using observed data over the period 1996Q2 to 2013Q2 by applying Bayesian estimation techniques. The results suggest that a big part of the variation in inflation in India is due to cost-push shocks and, mainly during the years 2008 and 2010, also to global food price shocks, after having controlled for exogenous rainfall shocks. We conclude that the inflationary supply shocks (cost-push, oil price, domestic food price and global food price shocks) are important contributors to inflation in India. Since the monetary authority responds to these supply shocks with a higher interest rate which tends to slow growth, this raises concerns about how such output losses can be prevented by reducing exposure to commodity price shocks.
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Central Bank Transparency and Cross-border Banking
Stefan Eichler, Helge Littke, Lena Tonzer
Abstract
We analyze the effect of central bank transparency on cross-border bank activities. Based on a panel gravity model for cross-border bank claims for 21 home and 47 destination countries from 1998 to 2010, we find strong empirical evidence that a rise in central bank transparency in the destination country, on average, increases cross-border claims. Using interaction models, we find that the positive effect of central bank transparency on cross-border claims is only significant if the central bank is politically independent. Central bank transparency and credibility are thus considered complements by banks investing abroad.
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Nested Models and Model Uncertainty
Alexander Kriwoluzky, Christian A. Stoltenberg
Scandinavian Journal of Economics,
No. 2,
2016
Abstract
Uncertainty about the appropriate choice among nested models is a concern for optimal policy when policy prescriptions from those models differ. The standard procedure is to specify a prior over the parameter space, ignoring the special status of submodels (e.g., those resulting from zero restrictions). Following Sims (2008, Journal of Economic Dynamics and Control 32, 2460–2475), we treat nested submodels as probability models, and we formalize a procedure that ensures that submodels are not discarded too easily and do matter for optimal policy. For the United States, we find that optimal policy based on our procedure leads to substantial welfare gains compared to the standard procedure.
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Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information
Christiane Baumeister, James D. Hamilton
Econometrica,
No. 5,
2015
Abstract
This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.
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Global Food Prices and Business Cycle Dynamics in an Emerging Market Economy
Oliver Holtemöller, Sushanta Mallick
Abstract
This paper investigates a perception in the political debates as to what extent poor countries are affected by price movements in the global commodity markets. To test this perception, we use the case of India to establish in a standard SVAR model that global food prices influence aggregate prices and food prices in India. To further analyze these empirical results, we specify a small open economy New-Keynesian model including oil and food prices and estimate it using observed data over the period from 1996Q2 to 2013Q2 by applying Bayesian estimation techniques. The results suggest that big part of the variation in inflation in India is due to cost-push shocks and, mainly during the years 2008 and 2010, also to global food price shocks, after having controlled for exogenous rainfall shocks. We conclude that the inflationary supply shocks (cost-push, oil price, domestic food price and global food price shocks) are important contributors to inflation in India. Since the monetary authority responds to these supply shocks with a higher interest rate which tends to slow growth, this raises concerns about how such output losses can be prevented by reducing exposure to commodity price shocks and thereby achieve higher growth.
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Young, Restless and Creative: Openness to Disruption and Creative Innovations
Daron Acemoglu, Ufuk Akcigit, Murat Alp Celik
NBER Working Paper,
No. 19894,
2015
Abstract
This paper argues that openness to new, unconventional and disruptive ideas has a first-order impact on creative innovations—innovations that break new ground in terms of knowledge creation. After presenting a motivating model focusing on the choice between incremental and radical innovation, and on how managers of different ages and human capital are sorted across different firms with different degrees of openness to disruption, we provide firm-level, patent level and cross-country evidence consistent with this pattern. Our measures of creative innovations proxy for innovation quality (average number of citations per patent) and creativity (fraction of superstar innovators, the likelihood of a very high number of citations, and generality of patents). Our main proxy for openness to disruption is the age of the manager - based on the idea that only companies or societies open to such disruption will allow the young to rise up within the hierarchy. Using this proxy at the firm, patent and country level, we present robust evidence that openness to disruption is associated with more creative innovations, but we also show that once the effect of the sorting of young managers to firms that are more open to disruption is factored in, the (causal) impact of manager age on creative innovations is small.
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Returns to Skills around the World: Evidence from PIAAC
Eric A. Hanushek, Guido Schwerdt, Simon Wiederhold, Ludger Woessmann
European Economic Review,
January
2015
Abstract
Existing estimates of the labor-market returns to human capital give a distorted picture of the role of skills across different economies. International comparisons of earnings analyses rely almost exclusively on school attainment measures of human capital, and evidence incorporating direct measures of cognitive skills is mostly restricted to early-career workers in the United States. Analysis of the new PIAAC survey of adult skills over the full lifecycle in 23 countries shows that the focus on early-career earnings leads to underestimating the lifetime returns to skills by about one quarter. On average, a one-standard-deviation increase in numeracy skills is associated with an 18 percent wage increase among prime-age workers. But this masks considerable heterogeneity across countries. Eight countries, including all Nordic countries, have returns between 12 and 15 percent, while six are above 21 percent with the largest return being 28 percent in the United States. Estimates are remarkably robust to different earnings and skill measures, additional controls, and various subgroups. Instrumental-variable models that use skill variation stemming from school attainment, parental education, or compulsory-schooling laws provide even higher estimates. Intriguingly, returns to skills are systematically lower in countries with higher union density, stricter employment protection, and larger public-sector shares.
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Macroeconomic Factors and Micro-Level Bank Risk
Claudia M. Buch
Bundesbank Discussion Paper 20/2010,
2010
Abstract
The interplay between banks and the macroeconomy is of key importance for financial and economic stability. We analyze this link using a factor-augmented vector autoregressive model (FAVAR) which extends a standard VAR for the U.S. macroeconomy. The model includes GDP growth, inflation, the Federal Funds rate, house price inflation, and a set of factors summarizing conditions in the banking sector. We use data of more than 1,500 commercial banks from the U.S. call reports to address the following questions. How are macroeconomic shocks transmitted to bank risk and other banking variables? What are the sources of bank heterogeneity, and what explains differences in individual banks’ responses to macroeconomic shocks? Our paper has two main findings: (i) Average bank risk declines, and average bank lending increases following expansionary shocks. (ii) The heterogeneity of banks is characterized by idiosyncratic shocks and the asymmetric transmission of common shocks. Risk of about 1/3 of all banks rises in response to a monetary loosening. The lending response of small, illiquid, and domestic banks is relatively large, and risk of banks with a low degree of capitalization and a high exposure to real estate loans decreases relatively strongly after expansionary monetary policy shocks. Also, lending of larger banks increases less while risk of riskier and domestic banks reacts more in response to house price shocks.
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Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment
Katja Drechsel, Rolf Scheufele
Abstract
This paper presents a method to conduct early estimates of GDP growth in Germany. We employ MIDAS regressions to circumvent the mixed frequency problem and use pooling techniques to summarize efficiently the information content of the various indicators. More specifically, we investigate whether it is better to disaggregate GDP (either via total value added of each sector or by the expenditure side) or whether a direct approach is more appropriate when it comes to forecasting GDP growth. Our approach combines a large set of monthly and quarterly coincident and leading indicators and takes into account the respective publication delay. In a simulated out-of-sample experiment we evaluate the different modelling strategies conditional on the given state of information and depending on the model averaging technique. The proposed approach is computationally simple and can be easily implemented as a nowcasting tool. Finally, this method also allows retracing the driving forces of the forecast and hence enables the interpretability of the forecast outcome.
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