Comparing Financial Transparency between For-profit and Nonprofit Suppliers of Public Goods: Evidence from Microfinance
John W. Goodell, Abhinav Goyal, Iftekhar Hasan
Journal of International Financial Markets, Institutions and Money,
January
2020
Abstract
Previous research finds market financing is favored over relationship financing in environments of better governance, since the transaction costs to investors of vetting asymmetric information are thereby reduced. For industries supplying public goods, for-profits rely on market financing, while nonprofits rely on relationships with donors. This suggests that for-profits will be more inclined than nonprofits to improve financial transparency. We examine the impact of for-profit versus nonprofit status on the financial transparency of firms engaged with supplying public goods. There are relatively few industries that have large number of both for-profit and nonprofit firms across countries. However, the microfinance industry provides the opportunity of a large number of both for-profit and nonprofit firms in relatively equal numbers, across a wide array of countries. Consistent with our prediction, we find that financial transparency is positively associated with a for-profit status. Results will be of broad interest both to scholars interested in the roles of transparency and transaction costs on market versus relational financing; as well as to policy makers interested in the impact of for-profit on the supply of public goods, and on the microfinance industry in particular.
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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics,
Nr. 1,
2020
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Predicting Free-riding in a Public Goods Game – Analysis of Content and Dynamic Facial Expressions in Face-to-Face Communication
Dmitri Bershadskyy, Ehsan Othman, Frerk Saxen
IWH Discussion Papers,
Nr. 9,
2019
Abstract
This paper illustrates how audio-visual data from pre-play face-to-face communication can be used to identify groups which contain free-riders in a public goods experiment. It focuses on two channels over which face-to-face communication influences contributions to a public good. Firstly, the contents of the face-to-face communication are investigated by categorising specific strategic information and using simple meta-data. Secondly, a machine-learning approach to analyse facial expressions of the subjects during their communications is implemented. These approaches constitute the first of their kind, analysing content and facial expressions in face-to-face communication aiming to predict the behaviour of the subjects in a public goods game. The analysis shows that verbally mentioning to fully contribute to the public good until the very end and communicating through facial clues reduce the commonly observed end-game behaviour. The length of the face-to-face communication quantified in number of words is further a good measure to predict cooperation behaviour towards the end of the game. The obtained findings provide first insights how a priori available information can be utilised to predict free-riding behaviour in public goods games.
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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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The Forward-looking Disclosures of Corporate Managers: Theory and Evidence
Reint E. Gropp, Rasa Karapandza, Julian Opferkuch
IWH Discussion Papers,
Nr. 25,
2016
Abstract
We consider an infinitely repeated game in which a privately informed, long-lived manager raises funds from short-lived investors in order to finance a project. The manager can signal project quality to investors by making a (possibly costly) forward-looking disclosure about her project’s potential for success. We find that if the manager’s disclosures are costly, she will never release forward-looking statements that do not convey information to external investors. Furthermore, managers of firms that are transparent and face significant disclosure-related costs will refrain from forward-looking disclosures. In contrast, managers of opaque and profitable firms will follow a policy of accurate disclosures. To test our findings empirically, we devise an index that captures the quantity of forward-looking disclosures in public firms’ 10-K reports, and relate it to multiple firm characteristics. For opaque firms, our index is positively correlated with a firm’s profitability and financing needs. For transparent firms, there is only a weak relation between our index and firm fundamentals. Furthermore, the overall level of forward-looking disclosures declined significantly between 2001 and 2009, possibly as a result of the 2002 Sarbanes-Oxley Act.
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On the Trail of Core–periphery Patterns in Innovation Networks: Measurements and New Empirical Findings from the German Laser Industry
Wilfried Ehrenfeld, Toralf Pusch, Muhamed Kudic
Annals of Regional Science,
Nr. 1,
2015
Abstract
It has been frequently argued that a firm’s location in the core of an industry’s innovation network improves its ability to access information and absorb technological knowledge. The literature has still widely neglected the role of peripheral network positions for innovation processes. In addition to this, little is known about the determinants affecting a peripheral actors’ ability to reach the core. To shed some light on these issues, we have employed a unique longitudinal dataset encompassing the entire population of German laser source manufacturers (LSMs) and laser-related public research organizations (PROs) over a period of more than two decades. The aim of our paper is threefold. First, we analyze the emergence of core–periphery (CP) patterns in the German laser industry. Then, we explore the paths on which LSMs and PROs move from isolated positions toward the core. Finally, we employ non-parametric event history techniques to analyze the extent to which organizational and geographical determinates affect the propensity and timing of network core entries. Our results indicate the emergence and solidification of CP patterns at the overall network level. We also found that the paths on which organizations traverse through the network are characterized by high levels of heterogeneity and volatility. The transition from peripheral to core positions is impacted by organizational characteristics, while an organization’s geographical location does not play a significant role.
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Stale Information, Shocks, and Volatility
Reint E. Gropp, A. Kadareja
Journal of Money, Credit and Banking,
Nr. 6,
2012
Abstract
We propose a new approach to measuring the effect of unobservable private information on volatility. Using intraday data, we estimate the effect of a well-identified shock on the volatility of stock returns of European banks as a function of the quality of public information available about the banks. We hypothesize that as publicly available information becomes stale, volatility effects and its persistence increase, as private information of investors becomes more important. We find strong support for this idea in the data. We further show that stock volatility is higher just before important announcements if information is stale.
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Competition, Risk-shifting, and Public Bail-out Policies
Reint E. Gropp, H. Hakenes, Isabel Schnabel
Review of Financial Studies,
Nr. 6,
2011
Abstract
This article empirically investigates the competitive effects of government bail-out policies. We construct a measure of bail-out perceptions by using rating information. From there, we construct the market shares of insured competitor banks for any given bank, and analyze the impact of this variable on banks' risk-taking behavior, using a large sample of banks from OECD countries. Our results suggest that government guarantees strongly increase the risk-taking of competitor banks. In contrast, there is no evidence that public guarantees increase the protected banks' risk-taking, except for banks that have outright public ownership. These results have important implications for the effects of the recent wave of bank bail-outs on banks' risk-taking behavior.
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Analyzing Innovation Drivers in the German Laser Industry: the Role of Positioning in the Social and Geographical Space
Muhamed Kudic, Peter Bönisch, Iciar Dominguez Lacasa
Abstract
Empirical and theoretical contributions provide strong evidence that firm-level performance outcomes in terms of innovativeness can either be determined by the firm’s position in the social space (network effects) or by the firm’s position in the geographical space (co-location effects). Even though we can observe quite recently first attempts in bringing together these traditionally distinct research streams (Whittington et al. 2009), research on interdependent network and geographical co-location effects is still rare. Consequently, we seek to answer the following research question: considering that the effects of social and geographic proximity on firm’s innovativeness can be interdependent, what are the distinct and combined effects of firm’s network and geographic position on firm-level innovation output? We analyze the innovative performance of German laser source manufacturers between 1995 and 2007. We use an official database on publicly funded R&D collaboration projects in order to construct yearly networks and analyze firm’s network positions. Based on information on population entries and exits we calculate various types of geographical proximity measures between private sector and public research organizations (PRO). We use patent grants as dependent variable in order to measure firm-level innovation output. Empirical results provide evidence for distinct effect of network degree centrality. Distinct effect of firm’s geographical co-location to laser-related public research organization promotes patenting activity. Results on combined network and co-location effects confirms partially the existence of in-terdependent proximity effects, even though a closer look at these effects reveals some ambiguous but quite interesting findings.
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