Innovation,finance, and economic growth: an agent-based approach

This paper extends the endogenous growth agent-based model in Fagiolo and Dosi (Struct Change Econ Dyn 14(3):237–273, 2003) to study the finance–growth nexus. We explore industries where firms produce a homogeneous good using existing technologies, perform R&D activities to introduce new techniques, and imitate the most productive practices. Unlike the original model, we assume that both exploration and imitation require resources provided by banks, which pool agent savings and finance new projects via loans. We find that banking activity has a positive impact on growth. However, excessive financialization can hamper growth. Indeed, we find a significant and robust inverted U-shaped relation between financial depth and growth. Overall, our results stress the fundamental (and still poorly understood) role played by innovation in the finance–growth nexus.

     

Hypothesis testing in nonparametric models of production using multiple sample splits

Several tests of model structure developed by Kneip et al. (J Bus Econ Stat 34:435–456, 2016) and Daraio et al. (Econ J 21:170–191, 2018) rely on comparing sample means of two different efficiency estimators, one appropriate under the conditions of the null hypothesis and the other appropriate under the conditions of the alternative hypothesis. These tests rely on central limit theorems developed by Kneip et al. (Econ Theory 31:394–422, 2015) and Daraio et al. (Econ J 21:170–191, 2018), but require that the original sample be split randomly into two independent subsamples. This introduces some ambiguity surrounding the sample-split, which may be determined by choice of a seed for a random number generator. We develop a method that eliminates much of this ambiguity by repeating the random splits a large number of times. We use a bootstrap algorithm to exploit the information from the multiple sample-splits. Our simulation results show that in many cases, eliminating this ambiguity results in tests with better size and power than tests that employ a single sample-split.

     

Decomposition of technical efficiency under fixed proportion technologies: an application of data envelopment analysis

In this paper, we extend the four-component stochastic frontier model to allow for global spatial dependence via the endogenous spatial autoregressive variable. Our proposed model is more general than the model considered by (Glass et al., 2016) in the sense that we include a random effect as well as a permanent efficiency component. With the spatial autoregressive specification, our model is able to capture the asymmetric efficiency spillovers and also decompose the persistent/transient inefficiencies into direct and indirect efficiencies. Moreover, we also investigate the marginal effects of the exogenous variables on the persistent/transient efficiency. We suggest a maximum simulated likelihood method to estimate the frontier parameters of the model, and we predict the efficiencies using the simulated estimator. Monte Carlo simulations reveal that the suggested estimator performs well in finite samples. An empirical application is considered to illustrate the usefulness of our proposed model and method.

     

Big data for corporate social responsibility: blockchain use in Gioia del Colle DOP

The traceability of the supply chain with strict compliance with the specification to demonstrate in "transparency" the production processes in compliance with legislation and from a corporate social responsibility perspective, represents a fundamental requirement at the basis of competitive advantage in the food industries (Patelli and Mandrioli, J Food Sci 85: 3670–3678, 2020). The purpose of this work is to illustrate the innovative method for the certification and protection of the production phases of the DOP food chain and specifically the Mozzarella DOP of Gioia del Colle produced by the company Capurso Azienda Casearia Srl. This innovative approach consists of several phases that will be described in detail in the following paper. Besides, the idea of the introduction of Blockchain technology in an industry like this is an important step. This technology, associated with more accurate and intelligent management of the data acquisition process (Big data approach), optimizes the productivity of small businesses such as the dairy company. Blockchain technology guarantees security in the management of large amounts of data as never before possible, an innovative and experimental approach that makes the entire path of the production chain more controlled and optimized (Giacalone et al. International workshop on fuzzy logic and applications. Springer, Cham, pp. 218–225, 2016).

     

Contagion of network products in small-world networks

We formulate a model in which agents embedded in an exogenous social network decide whether to adopt a new network product or not. In the theoretical part of the paper, we characterize the stochastically stable equilibria for complete networks and cycles. For an arbitrary network structure, we develop a novel graph decomposition method to characterize the set of recurrent communication states, which is a superset of stochastically stable equilibria of the adoption game presented in our model. In the simulation part, we study the contagion process of a network product in small-world networks that systematically represent social networks. We simulate a generalization of the Morris (Rev Econ Stud 67(1):57–78, 2000) Contagion model that can explain the chasm between early adopters and early majority. Our numerical analysis shows that the failure of a new network product is less likely in a highly cliquish network. In addition, the contagion process reaches to steady state faster in random networks than in highly cliquish networks. It turns out that marketers should work with mixed marketing strategies, which will result in a full contagion of a network product and faster contagion rates with a higher probability.

     

Revisiting the issue of survivability and market efficiency with the Santa Fe Artificial Stock Market

The relevance of risk preference and forecasting accuracy for investor survival has recently been the focus of a series of theoretical and simulation studies. At one extreme, it has been proven that risk preference can be entirely irrelevant (Sandroni in Econometrica 68:1303–1341, 2000; Blume and Easley in Econometrica 74(4):929–966, 2006). However, the agent-based computational approach indicates that risk preference matters and can be more relevant for survivability than forecasting accuracy (Chen and Huang in Advances in natural computation, Springer, Berlin, 2005; J Econ Behav Organ 67(3):702–717, 2008; Huang in J Econ Interact Coord, 2015). Chen and Huang (Inf Sci 177(5):1222–1229, 2007, 2008) further explained that it is the saving behavior of traders that determines their survivability. However, institutional investors do not have to consider saving decisions that are the most influential investors in modern financial markets. Additionally, traders in the above series of theoretical and simulation studies have learned to forecast the stochastic process that determines which asset will pay dividends, not the market prices and dividends. To relate the research on survivability to issues with respect to the efficient markets hypothesis, it is better to endow agents with the ability to forecast market prices and dividends. With the Santa Fe Artificial Stock Market, where traders do not have to consider saving decisions and can learn to forecast both asset prices and dividends, we revisit the issue of survivability and market efficiency. We find that the main finding of Chen and Huang (2008) that risk preference is much more relevant for survivability than forecasting accuracy still holds for a wide range of market conditions but can fail when the baseline dividend becomes very small. Moreover, the advantage of traders who are less averse to risk is revealed in the market where saving decisions are not taken into account. Finally, Huang’s (2015) argument regarding the degree of market inefficiency is confirmed.     

Entrepreneurial ecosystems and the lifecycle of university business incubators: An integrative case study

University business incubators (UBIs) are an important part of the ecosystem that supports entrepreneurial activities and economic development. Extant research has focused on examining UBI activities at a single point in time, but there is a paucity of theoretical and empirical work aimed at understanding the forces that explain why and how UBIs change over time. This is an important gap because establishing a university business incubator does not assure its development and growth. We address this issue by drawing upon the Fisher et al. Academy of Management Review, 41(3), 383-409 (2016) Identity-Legitimacy-Life Cycle model to explain how the pursuit of resources and organizational legitimacy shapes the development of UBIs along key strategic and operational dimensions, which has implications for performance evaluation over time. We illustrate with a case study about the creation and evolution of the DMZ, a leading UBI at Ryerson University in Canada. This case provides new insights about the dynamics of UBIs and their relationships with the entrepreneurial ecosystems in which they are embedded. Implications for future research, management practice, and public policy are discussed.

     

Learning to save in a voluntary pension system: toward an agent-based model

Mandatory pension systems partially replace old-age income, therefore the government matches additional life-cycle savings in a voluntary pension system. Though the individual saving decisions are apparently independent, the earmarked taxes (paid to finance the matching) connect them. Previous models either neglected the endogenous tax expenditures (e.g. Choi et al., in: Wise (ed) Perspectives in the economics of aging, University of Chicago Press, Chicago, pp 81–121, 2004) or assumed very sophisticated saving strategies (e.g. Fehr et al. in FinanzArchiv Pub Finance Anal 64:171–198, 2008). We create twin models: myopic workers learn (i) from farsighted workers using public information (analytic model) and (ii) also from each other (agent-based model). These models provide more realistic results on saving behavior and the impact of matching on the income redistribution than the earlier models.

     

Persistence of financial efficiency in indian hospitality and tourism industry: a dynamic panel Approach

This paper analyses the degree of persistence of financial efficiency for the hospitality and tourism industry in India. The paper deploys the Data Envelopment Analysis technique to generate overall technical efficiency scores as well as pure technical efficiency scores. Furthermore, a dynamic panel technique proposed by Arellano and Bond (1991), is employed to test the degree of persistence of financial efficiency and its key determinants. The results confirm positive and significant persistence of efficiency for the sample firms from the hospitality industry in India. The overall results indicate that hospitality firms in India can create entry and exit barriers to generate positive persistence of financial efficiency. The study suggests regulators specifically focus on policies that can enhance the competitive dynamics of the industry. Such measures may make it imperative for the management of the firms in the sector to streamline their financial management policies to control costs and devise methods for the enhancement of revenues.

     

Social Media Screening and Procedural Justice: Towards Fairer Use of Social Media in Selection

Companies have started using social media for screening applicants in the selection process. Thereby, they enter a low-cost source of information on applicants, which potentially allows them to hire the right person on the job and avoid irresponsible employee behaviour and negligent hiring lawsuits. However, a number of ethical issues are associated with this practice, which give rise to the question of the fairness of social media screening. This article aims to provide an assessment of the procedural justice of social media screening and to articulate recommendations for a fairer use of social media in the selection process. To achieve this, a systematic literature review of research articles pertaining to social media screening has been conducted. Thereby, the benefits and ethical issues relating to social media screening, as well as recommendations for its use have been extracted and discussed against Leventhal’s (1980) rules of procedural justice. It turns out that without clear guidelines for recruiters, social media screening cannot be considered procedurally fair, as it opens up way too many opportunities for infringements on privacy, unfair discrimination, and adverse selection based on inaccurate information. However, it is possible to enhance the fairness of this practice by establishing clear policies and procedures to standardize the process.

     

Relationship between entrepreneurial orientation and social performance in Spanish sports clubs. The effect of the type of funding and the level of competition

The entrepreneurial orientation and social role of sports clubs have recently become topics of great interest to academics and professionals. The aim of this study is to analyse the relationship between entrepreneurial orientation (EO) in sports clubs and their social performance (SP) and the effect that management variables such as the type of funding (public vs private) and the competition level (national vs regional) may have on this relationship. To compare the results, two complementary methodologies have been used to compare the results: linear models with moderation analysis and models based on qualitative comparative analysis (QCA). The study was carried out with a sample of 407 Spanish sports clubs. The instrument used to measure EO was an adaptation of the original Covin and Slevin (1989) approach, while the instrument used to measure SP is a validated scale of our own elaboration presenting good psychometric properties. The results found show a direct effect of the EO dimensions on the SP. In all cases, clubs with major public funding showed higher levels of prediction in SP. On the other hand, as far as QCA is concerned, no necessary condition was found, while the most important condition sufficient to obtain high levels of SP would be high levels of innovation, a high level of risk-taking, and low levels of proactivity in national sports clubs. In general, models based on qualitative comparative analysis (QCA) provide higher predictive values than linear regression models and include variables not considered in linear models.

     

Statistical model for earthquake economic loss estimation using GDP and DPI: a case study from Iran

As earthquakes can result in multi-dimensional negative consequences such as human loss and building damage, the ability to make accurate economic loss estimations immediately after the occurrence is crucial. Unfortunately, in many earthquake-stricken countries such as Iran, governments are often unable to quickly or accurately assess post-earthquake losses. The aim of this paper, therefore, is to extend the model developed by Chan et al. (Nat Hazards 17:269–283, 1998) to two independent variables to develop an earthquake economic loss estimation method based on the economic and socio-economic indices gross domestic product (GDP) and disposable personal income (DPI) and a seismic hazard probability function. A global cell map is also considered to assess the GDP and DPI based on the population in each cell affected by the earthquake. In the final stage, using the Modified Mercalli Intensity Scale, 18 earthquake damaged areas in Iran are taken as case study to estimate the economic losses using the new model presented in this paper.

     

The effect of firm complexity and founding team size on agile internal communication in startups

Today’s firms, particularly startups, require agile communication to sense and seize opportunities and to adapt to the market as quickly as possible (Picken 2017; Takeuchi and Nonaka 1986). However, scholars have predominantly focused on external communication, taking agile internal communication for granted. This paper analyzes the combinations of conditions (i.e., firm features and communication devices) that are present in startups with agile internal communication. The study considers the startup’s life cycle, the size of the startup, and the size of the founding team. The use of direct communication channels, structured communication channels, and agile methods is also considered. Analysis of 88 Spanish startups shows that the size of the founding team influences the combination of present and absent communication methods when agile internal communication is present. In startups where the founding team is small, direct communication methods are absent, whereas the use of structured communication methods, online project management, and other communication tools is present. On the contrary, when the founding team size is large, direct communication is a core condition, as is the absence of structured communication methods. Agile methods represent a peripheral condition for the presence of agile internal communication when the founding team is small and structured communication is present as a core condition. Similarly, when the founding team is small and the presence of direct communication is a core condition, the presence of agile methods is a peripheral condition for the presence of agile internal communication.

     

Competing mechanism games of moral hazard: communication and robustness

We consider multiple-principal multiple-agent models of moral hazard: principals compete through mechanisms in the presence of agents who take unobservable actions. In this context, we provide a rationale for restricting principals to make use of simple mechanisms, which correspond to direct mechanisms in the standard framework of Myerson (J Math Econ 10:67–81, 1982). Our results complement those of Han (J Econ Theory 137(1):610–626, 2007) who analyzes a complete information setting where agents’ actions are fully contractible.     

Persistent and transient productive inefficiency: a maximum simulated likelihood approach

The productive efficiency of a firm can be seen as composed of two parts, one persistent and one transient. The received empirical literature on the measurement of productive efficiency has paid relatively little attention to the difference between these two components. Ahn and Sickles (Econ Rev 19(4):461–492, 2000) suggested some approaches that pointed in this direction. The possibility was also raised in Greene (Health Econ 13(10):959–980, 2004. doi:10.1002/hec.938), who expressed some pessimism over the possibility of distinguishing the two empirically. Recently, Colombi (A skew normal stochastic frontier model for panel data, 2010) and Kumbhakar and Tsionas (J Appl Econ 29(1):110–132, 2012), in a milestone extension of the stochastic frontier methodology have proposed a tractable model based on panel data that promises to provide separate estimates of the two components of efficiency. The approach developed in the original presentation proved very cumbersome actually to implement in practice. Colombi (2010) notes that FIML estimation of the model is ‘complex and time consuming.’ In the sequence of papers, Colombi (2010), Colombi et al. (A stochastic frontier model with short-run and long-run inefficiency random effects, 2011, J Prod Anal, 2014), Kumbhakar et al. (J Prod Anal 41(2):321–337, 2012) and Kumbhakar and Tsionas (2012) have suggested other strategies, including a four step least squares method. The main point of this paper is that full maximum likelihood estimation of the model is neither complex nor time consuming. The extreme complexity of the log likelihood noted in Colombi (2010), Colombi et al. (2011, 2014) is reduced by using simulation and exploiting the Butler and Moffitt (Econometrica 50:761–764, 1982) formulation. In this paper, we develop a practical full information maximum simulated likelihood estimator for the model. The approach is very effective and strikingly simple to apply, and uses all of the sample distributional information to obtain the estimates. We also implement the panel data counterpart of the Jondrow et al. (J Econ 19(2–3):233–238, 1982) estimator for technical or cost inefficiency. The technique is applied in a study of the cost efficiency of Swiss railways.     

An alternative approach to housing market segmentation using hedonic price data

Much empirical research has been devoted to housing market segmentation and the implications for the application of the Hedonic Price Model. Market segmentation is demonstrated empirically in (J. Urban Econ., 3:2, 146–166 (1976); J. Urban Econ., 7:1, 102–108 (1980); Rev. Econ. Statist., 66:3, 404–406 (1974)). There appears to be theoretical evidence (J. Pol. Econ., 82:1, 34–55 (1974)) that such empirical efforts may have been less than adequate. Unfortunately, the empirical applications of Rosen's model (J. Environ. Econ. Manag., 5, 81–102 (1978); J. Urban Econ., 5, 3, 357–369 (1978)) do not seem to effectively account for the complexity of the factors which cause multiple equilibria (market segmentation). This paper demonstrates empirically that market segments can be defined along more dimensions than hitherto have been included in any analysis.     

Financial Support for Family Members and Importance of Performance Quality Interact as a Source of Motivation for Multiple Jobholding

Very few studies on multiple jobholding have examined predictors. Most studies have focused on outcomes. The current study examined an interactive predictor of multiple jobholding. Data were extracted from a data set used in a path-analytic study (Mellor and Decker 2020). An interactive perspective was drawn from a motivation framework on extrinsic and intrinsic reasons to hold more than one job, in which a conditional relationship was hypothesized between number of family members supported financially and number of employers. The data confirmed that number of family members supported interacts with importance placed on performance quality by employees as a predictor of multiple jobholding. Implications for work motivation in reference to multiple jobholding research are discussed.

     

Non-self-averaging of a two-person game with only positive spillover: a new formulation of Avatamsaka’s dilemma

In this game [Aruka in Avatamsaka game structure and experiment on the web. In: Aruka Y (ed) Evolutionary controversies in economics. Springer, Tokyo, pp 115–132, 2001], selfishness may not be determined even if an agent selfishly adopts the strategy of defection. Individual selfishness can only be realized if the other agent cooperates, therefore gain from defection can never be assured by defection alone. The sanction by defection as a reaction of the rival agent cannot necessarily reduce the selfishness of the rival. In this game, explicit direct reciprocity cannot be guaranteed. Now we introduce different spillovers or payoff matrices, so that each agent may then be faced with a different payoff matrix. A ball in the urn is interpreted as the number of cooperators, and the urn as a payoff matrix. We apply Ewens’ sampling formula to our urn process in this game theoretic environment. In this case, there is a similar result as in the classic case, because there is “self-averaging” for the variances of the number who cooperate. Applying Pitman’s sampling formula to the urn process, the invariance of the random partition vectors under the properties of exchangeability and size-biased permutation does not hold in general. Pitman’s sampling formula depends on the two-parameter Poisson–Dirichlet distribution whose special case is just Ewens’ formula. In the Ewens setting, only one probability α of a new entry matters. On the other hand, there is an additional probability θ of an unknown entry, as will be argued in the Pitman formula. More concretely, we will investigate the effects of different payoff sizes from playing a series of different games for newly emerging agents. As Aoki and Yoshikawa (Non-self-averaging in macroeconomic models: a criticism of modern micro-founded macroeconomics, Economics Discussion Papers 2007-49. . November 26, 2007) and Aoki (J Econ Interact Coord 3:1–3, 2008) dealt with a product innovation and a process innovation, they criticized Lucas’ representative method and the idea that players face micro shocks drawn from the same unchanged probability distribution. In the light of Aoki and Yoshikawa (Non-self-averaging in macroeconomic models: a criticism of modern micro-founded macroeconomics, Economics Discussion Papers 2007-49. . November 26, 2007), we show the same argument in our Avatamsaka game with different payoffs. In this setting, innovations occurring in urns may be regarded as increases of the number of cooperators in urns whose payoffs are different.     

The influence of the media on the history of business success

All the main indicators related to entrepreneurship have increased since 2011 (Global Entrepreneurship Monitor 2018, 2019). The positive perception of this phenomenon was boosted by the socio-economic situation and by a specific agent of the entrepreneurial ecosystem: the economic specialized media. The aim of this study is to demonstrate that the economic media has given their readers an excessively positive discourse, linked to success and to the lack of analysis of the entrepreneurial phenomenon. The sample is defined in terms of a linguistic corpus comprising content related to entrepreneurship drawn from the digital editions of the three most important Spanish economic newspapers for the period 2010 to 2018. A systematic standardize assignment of categories to the contents and an analysis of the relationships between those categories has been carried out (Riffe et al. 2019). These categories are ‘number of contents’, ‘information treatment’, ‘percentage of success stories’, ‘percentage of content analysis’ and ‘sources’. The results reveal a clear intention of the media to offer an overly optimistic perception of the entrepreneurial phenomenon considering the survival rate of the projects mentioned. There is evidence for a selection of information linked to success, a lack of follow-up of the stories and a poor preparation by the media, which lacks specialized journalists and, above all, replicates agency contents. This study provides empirical evidence that helps to identify the optimistic perception imposed by the media for the entrepreneurial phenomenon. This perception, together with other relevant facts, contribute to the creation of an ‘information bubble’ (Cervantes-Zacarés 2019) during the period under study.

     

A bivariate infinitely divisible law for modeling the magnitude and duration of monotone periods of log‐returns

The focus of this article is modeling the magnitude and duration of monotone periods of log‐returns. For this, we propose a new bivariate law assuming that the probabilistic framework over the magnitude and duration is based on the joint distribution of (X,N), where N is geometric distributed and X is the sum of an identically distributed sequence of inverse‐Gaussian random variables independent of N. In this sense, X and N represent the magnitude and duration of the log‐returns, respectively, and the magnitude comes from an infinite mixture of inverse‐Gaussian distributions. This new model is named bivariate inverse‐Gaussian geometric ( in short) law. We provide statistical properties of the model and explore stochastic representations. In particular, we show that the is infinitely divisible, and with this, an induced Lévy process is proposed and studied in some detail. Estimation of the parameters is performed via maximum likelihood, and Fisher's information matrix is obtained. An empirical illustration to the log‐returns of Tyco International stock demonstrates the superior performance of the law compared to an existing model. We expect that the proposed law can be considered as a powerful tool in the modeling of log‐returns and other episodes analyses such as water resources management, risk assessment, and civil engineering projects.