The German Economy Continues its Downturn High inflation, increased interest rates, weak foreign demand and uncertainty...
Wirtschaft im Wandel
Wirtschaft im Wandel Die Zeitschrift „Wirtschaft im Wandel“ will eine breite...
IWH Discussion Papers,
In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
The State Expropriation Risk and the Pricing of Foreign Earnings
Journal of International Accounting Research,
We examine the pricing of U.S. multinational firms' foreign earnings in regard to their risk of expropriation and unfair treatment by the governments of the countries in which their international subsidiaries are located. Using 8,891 firm-years observations during the 2001–2013 period, we find that the value relevance of foreign earnings increases with the improvement of the protection from state expropriation risk in the subsidiary host-countries. Our results are not driven by the earnings management practice, investor distraction, country informativeness, and political and trade relationship of a foreign country with the U.S. Furthermore, our results are robust to the confounding effects of country factors, measurement error in the variable of the risk of expropriation, the influence of private contracting institutions, and endogeneity in the decision of the location of subsidiaries.
Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks
American Economic Review,
Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not.
Skills, Earnings, and Employment: Exploring Causality in the Estimation of Returns to Skills
Large-scale Assessments in Education,
Ample evidence indicates that a person’s human capital is important for success on the labor market in terms of both wages and employment prospects. However, unlike the efforts to identify the impact of school attainment on labor-market outcomes, the literature on returns to cognitive skills has not yet provided convincing evidence that the estimated returns can be causally interpreted. Using the PIAAC Survey of Adult Skills, this paper explores several approaches that aim to address potential threats to causal identification of returns to skills, in terms of both higher wages and better employment chances. We address measurement error by exploiting the fact that PIAAC measures skills in several domains. Furthermore, we estimate instrumental-variable models that use skill variation stemming from school attainment and parental education to circumvent reverse causation. Results show a strikingly similar pattern across the diverse set of countries in our sample. In fact, the instrumental-variable estimates are consistently larger than those found in standard least-squares estimations. The same is true in two “natural experiments,” one of which exploits variation in skills from changes in compulsory-schooling laws across U.S. states. The other one identifies technologically induced variation in broadband Internet availability that gives rise to variation in ICT skills across German municipalities. Together, the results suggest that least-squares estimates may provide a lower bound of the true returns to skills in the labor market.
„Challenges for Forecasting – Structural Breaks, Revisions and Measurement Errors” 16th IWH-CIREQ Macroeconometric Workshop
Wirtschaft im Wandel,
Am 7. und 8. Dezember 2015 fand am Leibniz-Institut für Wirtschaftsforschung Halle (IWH) zum 16. Mal der IWH-CIREQ Macroeconometric Workshop statt. Die in Kooperation mit dem Centre interuniversitaire de recherche en économie quantitative (CIREQ), Montréal, durchgeführte Veranstaltung beschäftigte sich dieses Mal mit zentralen Herausforderungen, denen sich die ökonomische Prognose zu stellen hat: Strukturbrüche in den Daten, statistische Revisionen und Fehler bei der Messung wichtiger Indikatoren.
The Quantity Theory Revisited: A New Structural Approach
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.