Plant-based Bioeconomy in Central Germany – A Mapping of Actors, Industries and Places
Wilfried Ehrenfeld, Frieder Kropfhäußer
Technology Analysis and Strategic Management,
No. 5,
2017
Abstract
The bioeconomy links industrial and agricultural research and production and is expected to provide growth, particularly in rural areas. However, it is still unclear which companies, research institutes and universities make up the bioeconomy. This makes it difficult to evaluate the policy measures that support the bioeconomy. The aim of this article is to provide an inventory of relevant actors in the three Central German states of Saxony, Saxony-Anhalt and Thuringia. First we take an in-depth look at the different sectors, outline the industries involved, note the location and age of the enterprises and examine the distribution of important European industrial activity classification (NACE) codes. Our results underline the fact that established industry classifications are insufficient in identifying the plant-based bioeconomy population. We also question the overly optimistic statements regarding growth potentials in rural areas and employment potentials in general.
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Skills, Earnings, and Employment: Exploring Causality in the Estimation of Returns to Skills
Franziska Hampf, Simon Wiederhold, Ludger Woessmann
Large-scale Assessments in Education,
No. 12,
2017
Abstract
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.
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Complex-task Biased Technological Change and the Labor Market
Colin Caines, Florian Hoffmann, Gueorgui Kambourov
Review of Economic Dynamics,
April
2017
Abstract
In this paper we study the relationship between task complexity and the occupational wage- and employment structure. Complex tasks are defined as those requiring higher-order skills, such as the ability to abstract, solve problems, make decisions, or communicate effectively. We measure the task complexity of an occupation by performing Principal Component Analysis on a broad set of occupational descriptors in the Occupational Information Network (O*NET) data. We establish four main empirical facts for the U.S. over the 1980–2005 time period that are robust to the inclusion of a detailed set of controls, subsamples, and levels of aggregation: (1) There is a positive relationship across occupations between task complexity and wages and wage growth; (2) Conditional on task complexity, routine-intensity of an occupation is not a significant predictor of wage growth and wage levels; (3) Labor has reallocated from less complex to more complex occupations over time; (4) Within groups of occupations with similar task complexity labor has reallocated to non-routine occupations over time. We then formulate a model of Complex-Task Biased Technological Change with heterogeneous skills and show analytically that it can rationalize these facts. We conclude that workers in non-routine occupations with low ability of solving complex tasks are not shielded from the labor market effects of automatization.
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Private Equity and Industry Performance
Shai B. Bernstein, Josh Lerner, Morten Sorensen, Per Strömberg
Management Science,
No. 4,
2017
Abstract
The growth of the private equity industry has spurred concerns about its impact on the economy. This analysis looks across nations and industries to assess the impact of private equity on industry performance. We find that industries where private equity funds invest grow more quickly in terms of total production and employment and appear less exposed to aggregate shocks. Our robustness tests provide some evidence that is consistent with our effects being driven by our preferred channel.
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Same, but Different: Testing Monetary Policy Shock Measures
Alexander Kriwoluzky, Stephanie Ettmeier
IWH Discussion Papers,
No. 9,
2017
Abstract
In this study, we test whether three popular measures for monetary policy, that is, Romer and Romer (2004), Barakchian and Crowe (2013), and Gertler and Karadi (2015), constitute suitable proxy variables for monetary policy shocks. To this end, we employ different test statistics used in the literature to detect weak proxy variables. We find that the measure derived by Gertler and Karadi (2015) is the most suitable in this regard.
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15.03.2017 • 13/2017
The German Economy: Employment Boom in Germany, but no Overheating of the Economy
Employment in Germany continues to increase healthily, and private consumption expands due to rising real incomes. Investment in equipment, however, remains modest. Overall, economic demand is expanding at roughly the growth rate of potential Gross Domestic Product (GDP), and the output gap is nearly closed. “In 2017, GDP will increase by 1.3% and thus at a lower rate than in the previous year, but this is only due to fewer working days and not to sliding demand,” says Oliver Holtemoeller, Head of the Department Macroeconomics and IWH vice president.
Oliver Holtemöller
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Taking the Leap: The Determinants of Entrepreneurs Hiring Their First Employee
Robert W. Fairlie, Javier Miranda
Journal of Economics and Management Strategy,
No. 1,
2017
Abstract
Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of start‐ups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a nonemployer to employer firm among start‐ups. Several interesting patterns emerge regarding the dynamics of nonemployer start‐ups hiring their first employee. Hiring rates among the universe of nonemployer start‐ups are very low, but increase when the population of nonemployers is focused on more growth‐oriented businesses such as incorporated and employer identification number businesses. If nonemployer start‐ups hire, the bulk of hiring occurs in the first few years of existence. After this point in time, relatively few nonemployer start‐ups hire an employee. Focusing on more growth‐ and employment‐oriented start‐ups in the KFS, we find that Asian‐owned and Hispanic‐owned start‐ups have higher rates of hiring their first employee than white‐owned start‐ups. Female‐owned start‐ups are roughly 10 percentage points less likely to hire their first employee by the first, second, and seventh years after start‐up. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that nonemployers hire their first employee.
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Should Forecasters Use Real-time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
Abstract
In this paper we investigate whether differences exist among forecasts using real-time or latest-available data to predict gross domestic product (GDP). We employ mixed-frequency models and real-time data to reassess the role of survey data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.
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On the Simultaneity Bias in the Relationship Between Risk Attitudes, Entry into Entrepreneurship and Entrepreneurial Survival
Matthias Brachert, Walter Hyll, Mirko Titze
Applied Economics Letters,
No. 7,
2017
Abstract
We consider the simultaneity bias when examining the effect of individual risk attitudes on entrepreneurship. We demonstrate that entry into self-employment is related to changes in risk attitudes. We further show that these changes are correlated with the probability to remain in entrepreneurship.
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