Productivity and Employment in APAC Economies: A Comparison With the EU Using Firm-Level Information
Hoang Minh Duy, Filippo di Mauro, Peter Morgan
ADBI Working Paper,
No. 1264,
2021
Abstract
We provide an overview of productivity development and other related indicators in Asia and Pacific (APAC) countries, with comparisons with the Europe region. We use the seventh vintage firm-level data from the Productivity Research Network in the APAC region and CompNet in Europe for our study. The overall results show that the productivity growth in developed APAC countries (Australia, New Zealand, and the Republic of Korea) is significantly ahead of the growth in developing APAC countries (India and the People’s Republic of China) and on par with the EU’s growth. There is an ongoing process of bottom firms catching up with top firms in the Republic of Korea and the richest EU countries. Regarding employment and labor skills, employment growth has generally been quite stagnant in all regions. Labor skills, for which we use the wage premium as a proxy, are quite similar across most regions, with the richest EU countries showing a higher premium than the rest. Our test of the productivity–employment link indicates that the size of employment tends to have a greater impact on productivity in APAC countries, while labor skills have greater emphasis in the EU.
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Local Banks as Difficult-to-replace SME Lenders: Evidence from Bank Corrective Programs
Iftekhar Hasan, Krzysztof Jackowicz, Robert Jagiełło, Oskar Kowalewski, Łukasz Kozłowski
Journal of Banking and Finance,
February
2021
Abstract
In this study, we assess capabilities of different types of banks to cater to the financial needs of small and medium-sized enterprises (SMEs). Using a comprehensive dataset from an emerging economy, including the information on local banks’ corrective programs, we find that local banks remain difficult-to-replace lenders for SMEs. We show that presence of healthy local banks in an SME's vicinity immunizes the SME against the deterioration of access to bank financing linked to other local banks’ corrective programs. In contrast, large banks are unable to replace the lost lending from local competitors under corrective programs.
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A Comparison of Monthly Global Indicators for Forecasting Growth
Christiane Baumeister, Pierre Guérin
Abstract
This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world GDP using mixed-frequency models. We find that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecast accuracy, while other monthly measures have more mixed success. This global economic conditions indicator contains valuable information also for assessing the current and future state of the economy for a set of individual countries and groups of countries. We use this indicator to track the evolution of the nowcasts for the US, the OECD area, and the world economy during the coronavirus pandemic and quantify the main factors driving the nowcasts.
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Private Equity and Portfolio Companies: Lessons From the Global Financial Crisis
Shai B. Bernstein, Josh Lerner, Filippo Mezzanotti
Journal of Applied Corporate Finance,
No. 3,
2020
Abstract
Critics of private equity have warned that the high leverage often used in PE-backed companies could contribute to the fragility of the financial system during economic crises. The proliferation of poorly structured transactions during booms could increase the vulnerability of the economy to downturns. The alternative hypothesis is that PE, with its operating capabilities, expertise in financial restructuring, and massive capital raised but not invested ("dry powder"), could increase the resilience of PE-backed companies. In their study of PE-backed buyouts in the U.K. - which requires and thereby makes accessible more information about private companies than, say, in the U.S. - the authors report finding that, during the 2008 global financial crisis, PE-backed companies decreased their overall investments significantly less than comparable, non-PE firms. Moreover, such PE-backed firms also experienced greater equity and debt inflows, higher asset growth, and increased market share. These effects were especially notable among smaller, riskier PE-backed firms with less access to capital, and also for those firms backed by PE firms with more dry powder at the crisis onset. In a survey of the partners and staff of some 750 PE firms, the authors also present compelling evidence that PEs firms play active financial and operating roles in preserving or restoring the profitability and value of their portfolio companies.
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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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