Connecting to Power: Political Connections, Innovation, and Firm Dynamics
Ufuk Akcigit, Salomé Baslandze, Francesca Lotti
NBER Working Paper,
Nr. 25136,
2018
Abstract
How do political connections affect firm dynamics, innovation, and creative destruction? To answer this question, we build a firm dynamics model, where we allow firms to invest in innovation and/or political connection to advance their productivity and to overcome certain market frictions. Our model generates a number of theoretical testable predictions and highlights a new interaction between static gains and dynamic losses from rent-seeking in aggregate productivity. We test the predictions of our model using a brand-new dataset on Italian firms and their workers, spanning the period from 1993 to 2014, where we merge: (i) firm-level balance sheet data; (ii) social security data on the universe of workers; (iii) patent data from the European Patent Office; (iv) the national registry of local politicians; and (v) detailed data on local elections in Italy. We find that firm-level political connections are widespread, especially among large firms, and that industries with a larger share of politically connected firms feature worse firm dynamics. We identify a leadership paradox: when compared to their competitors, market leaders are much more likely to be politically connected, but much less likely to innovate. In addition, political connections relate to a higher rate of survival, as well as growth in employment and revenue, but not in productivity – a result that we also confirm using a regression discontinuity design.
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Early-Stage Business Formation: An Analysis of Applications for Employer Identification Numbers
Kimberly Bayard, Emin Dinlersoz, Timothy Dunne, John Haltiwanger, Javier Miranda, John Stevens
NBER Working Paper,
Nr. 24364,
2018
Abstract
This paper reports on the development and analysis of a newly constructed dataset on the early stages of business formation. The data are based on applications for Employer Identification Numbers (EINs) submitted in the United States, known as IRS Form SS-4 filings. The goal of the research is to develop high-frequency indicators of business formation at the national, state, and local levels. The analysis indicates that EIN applications provide forward-looking and very timely information on business formation. The signal of business formation provided by counts of applications is improved by using the characteristics of the applications to model the likelihood that applicants become employer businesses. The results also suggest that EIN applications are related to economic activity at the local level. For example, application activity is higher in counties that experienced higher employment growth since the end of the Great Recession, and application counts grew more rapidly in counties engaged in shale oil and gas extraction. Finally, the paper provides a description of new public-use dataset, the “Business Formation Statistics (BFS),” that contains new data series on business applications and formation. The initial release of the BFS shows that the number of business applications in the 3rd quarter of 2017 that have relatively high likelihood of becoming job creators is still far below pre-Great Recession levels.
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Plant-based Bioeconomy in Central Germany – A Mapping of Actors, Industries and Places
Wilfried Ehrenfeld, Frieder Kropfhäußer
Technology Analysis and Strategic Management,
Nr. 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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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,
Nr. 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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Taking the Leap: The Determinants of Entrepreneurs Hiring Their First Employee
Robert W. Fairlie, Javier Miranda
Journal of Economics and Management Strategy,
Nr. 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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