Firm Productivity Report
Johannes Amlung, Tommaso Bighelli, Roman Blyzniuk, Marco Christophori, Jonathan Deist, Filippo di Mauro, Annalisa Ferrando, Mirja Hälbig, Peter Haug, Sergio Inferrera, Tibor Lalinsky, Phillip Meinen, Marc Melitz, Matthias Mertens, Ottavia Papagalli, Verena Plümpe, Roberta Serafini
CompNet - The Competitive Research Network,
2020
Abstract
As we enter a second phase of the COVID-pandemic, in which we attempt to reopen economies and foster growth, investigating the efficiency and productivity of firms becomes essential if we wish to design the appropriate policies. The 2020 Flagship Firm Productivity report provides a comprehensive account of how productivity is changing –and what is driving those changes –in Europe, drawing from granular firm-level information.Although it was written before the crisis erupted, this report can therefore offer critical insights to current policymaking andprovides grounds for future research.
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Bank Accounting Regulations, Enforcement Mechanisms, and Financial Statement Informativeness: Cross-country Evidence
Augustine Duru, Iftekhar Hasan, Liang Song, Yijiang Zhao
Accounting and Business Research,
No. 3,
2020
Abstract
We construct measures of accounting regulations and enforcement mechanisms that are specific to a country's banking industry. Using a sample of major banks in 37 economies, we find that the informativeness of banks’ financial statements, measured by the value relevance of earnings and common equity, is higher in countries with stricter bank accounting regulations and countries with stronger enforcement. These findings suggest that superior bank accounting and enforcement mechanisms enhance the informativeness of banks’ financial statements. In addition, we find that the effects of bank accounting regulations are more pronounced in countries with stronger enforcement in the banking industry, suggesting that enforcement is complementary to bank accounting regulations in achieving higher value relevance of financial statements. Our study has important policy implications for bank regulators.
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Does Machine Learning Help us Predict Banking Crises?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Journal of Financial Stability,
December
2019
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance measure, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly effciently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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Business Dynamics of Innovating Firms: Linking U.S. Patents with Administrative Data on Workers and Firms
Stuart Graham, Cheryl Grim, Tariqul Islam, Alan Marco, Javier Miranda
Journal of Economics and Management Strategy,
No. 3,
2018
Abstract
This paper discusses the construction of a new longitudinal database tracking inventors and patent-owning firms over time. We match granted patents between 2000 and 2011 to administrative databases of firms and workers housed at the U.S. Census Bureau. We use inventor information in addition to the patent assignee firm name to improve on previous efforts linking patents to firms. The triangulated database allows us to maximize match rates and provide validation for a large fraction of matches. In this paper, we describe the construction of the database and explore basic features of the data. We find patenting firms, particularly young patenting firms, disproportionally contribute jobs to the U.S. economy. We find that patenting is a relatively rare event among small firms but that most patenting firms are nevertheless small, and that patenting is not as rare an event for the youngest firms compared to the oldest firms. Although manufacturing firms are more likely to patent than firms in other sectors, we find that most patenting firms are in the services and wholesale sectors. These new data are a product of collaboration within the U.S. Department of Commerce, between the U.S. Census Bureau and the U.S. Patent and Trademark Office.
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Urban Occupational Structures as Information Networks: The Effect on Network Density of Increasing Number of Occupations
Shade T. Shutters, José Lobo, Rachata Muneepeerakul, Deborah Strumsky, Charlotta Mellander, Matthias Brachert, Teresa Farinha, Luis M. A. Bettencourt
Plos One,
forthcoming
Abstract
Urban economies are composed of diverse activities, embodied in labor occupations, which depend on one another to produce goods and services. Yet little is known about how the nature and intensity of these interdependences change as cities increase in population size and economic complexity. Understanding the relationship between occupational interdependencies and the number of occupations defining an urban economy is relevant because interdependence within a networked system has implications for system resilience and for how easily can the structure of the network be modified. Here, we represent the interdependencies among occupations in a city as a non-spatial information network, where the strengths of interdependence between pairs of occupations determine the strengths of the links in the network. Using those quantified link strengths we calculate a single metric of interdependence–or connectedness–which is equivalent to the density of a city’s weighted occupational network. We then examine urban systems in six industrialized countries, analyzing how the density of urban occupational networks changes with network size, measured as the number of unique occupations present in an urban workforce. We find that in all six countries, density, or economic interdependence, increases superlinearly with the number of distinct occupations. Because connections among occupations represent flows of information, we provide evidence that connectivity scales superlinearly with network size in information networks.
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TV and Entrepreneurship
Viktor Slavtchev, Michael Wyrwich
IWH Discussion Papers,
No. 17,
2017
Abstract
We empirically analyse whether television (TV) can influence entrepreneurial identity and incidence. To identify causal effects, we utilise a quasi-natural experiment setting. During the division of Germany after WWII into West Germany with a free-market economy and the socialistic East Germany with centrally-planned economy, some East German regions had access to West German public TV that – differently from the East German TV – transmitted images, values, attitudes and view of life compatible with the free-market economy principles and supportive of entrepreneurship. We show that during the 40 years of socialistic regime in East Germany entrepreneurship was highly regulated and virtually impossible and that the prevalent formal and informal institutions broke the traditional ties linking entrepreneurship to the characteristics of individuals so that there were hardly any differences in the levels and development of entrepreneurship between East German regions with and without West German TV signal. Using both, regional and individual level data, we show then that, for the period after the Unification in 1990 which made starting an own business in East Germany, possible again, entrepreneurship incidence is higher among the residents of East German regions that had access to West German public TV, indicating that TV can, while transmitting specific images, values, attitudes and view of life, directly impact on the entrepreneurial mindset of individuals. Moreover, we find that young individuals born after 1980 in East German households that had access to West German TV are also more entrepreneurial. These findings point to second-order effects due to inter-personal and inter-generational transmission, a mechanism that can cause persistent differences in the entrepreneurship incidence across (geographically defined) population groups.
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05.01.2017 • 3/2017
Secretariat for research network CompNet gets new home at IWH
The Halle Institute for Economic Research (IWH) – Member of the Leibniz Association is pleased to announce that it will be hosting the Secretariat for the Competitiveness Research Network (CompNet), an international network of scholars and practitioners, who share interest for top-notch research and policy analysis on competitiveness and productivity.
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Do Manufacturing Firms Benefit from Services FDI? – Evidence from Six New EU Member States
J. Damijan, Crt Kostevc, Philipp Marek, Matija Rojec
IWH Discussion Papers,
No. 5,
2015
Abstract
This paper focuses on the effect of foreign presence in the services sector on the productivity growth of downstream customers in the manufacturing sector in six EU new member countries in the course of their accession to the European Union. For this purpose, the analysis combines firm-level information, data on economic structures and annual national input-output tables. The findings suggest that services FDI may enhance productivity of manufacturing firms in Central and Eastern European (CEE) countries through vertical forward spillovers, and thereby contribute to their competitiveness. The consideration of firm characteristics shows that the magnitude of spillover effects depends on size, ownership structure, and initial productivity level of downstream firms as well as on the diverging technological intensity across sector on the supply and demand side. The results suggest that services FDI foster productivity of domestic rather than foreign controlled firms in the host economy. For the period between 2003 and 2008, the findings suggest that the increasing share of services provided by foreign affiliates enhanced the productivity growth of domestic firms in manufacturing by 0.16%. Furthermore, the firms’ absorptive capability and the size reduce the spillover effect of services FDI on the productivity of manufacturing firms. A sectoral distinction shows that firms at the end of the value chain experience a larger productivity growth through services FDI, whereas the aggregate positive effect seems to be driven by FDI in energy supply. This does not hold for science-based industries, which are spurred by foreign presence in knowledge-intensive business services.
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Assessing European Competitiveness: The New CompNet Microbased Database
Paloma Lopez-Garcia, Filippo di Mauro
ECB Working Paper,
No. 1764,
2015
Abstract
Drawing from confidential firm-level balance sheets for 17 European countries (13 Euro-Area), the paper documents the newly expanded database of cross-country comparable competitiveness-related indicators built by the Competitiveness Research Network (CompNet). The new database provides information on the distribution of labour productivity, TFP, ULC or size of firms in detailed 2-digit industries but also within broad macrosectors or considering the full economy. Most importantly, the expanded database includes detailed information on critical determinants of competitiveness such as the financial position of the firm, its exporting intensity, employment creation or price-cost margins. Both the distribution of all those variables, within each industry, but also their joint analysis with the productivity of the firm provides critical insights to both policy-makers and researchers regarding aggregate trends dynamics. The current database comprises 17 EU countries, with information for 56 industries, including both manufacturing and services, over the period 1995-2012. The paper aims at analysing the structure and characteristics of this novel database, pointing out a number of results that are relevant to study productivity developments and its drivers. For instance, by using covariances between productivity and employment the paper shows that the drop in employment which occurred during the recent crisis appears to have had “cleansing effects” on EU economies, as it seems to have accelerated resource reallocation towards the most productive firms, particularly in economies under stress. Lastly, this paper will be complemented by four forthcoming papers, each providing an in-depth description and methodological overview of each of the main groups of CompNet indicators (financial, trade-related, product and labour market).
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