nep-bec New Economics Papers
on Business Economics
Issue of 2023‒11‒06
ten papers chosen by
Vasileios Bougioukos, London South Bank University

  1. Identifying Nascent High-Growth Firms Using Machine Learning By Stephanie Houle; Ryan Macdonald
  2. Ownership Networks and Earnings Inequality By Huneeus, Federico; Larrain, Borja; Larrain, Mauricio; Prem, Mounu
  3. Do Large Firms Generate Positive Productivity Spillovers? By Mary Amiti; Cédric Duprez; Jozef Konings; John Van Reenen
  4. Are Immigrants Particularly Entrepreneurial? Policy Lessons from a Selective Immigration System By Green, David A.; Liu, Huju; Ostrovsky, Yuri; Picot, Garnett
  5. Acquisition Experience and the Winner’s Curse in Corporate Acquisitions By Marta Arroyabe; Katrin Hussinger
  6. Credit Supply Shocks and Firm Dynamics: Evidence from Brazil By Samuel Bazzi; Marc-Andreas Muendler; Raquel F. Oliveira; James Rauch; James E. Rauch
  7. Firm-Level Consequences of Export Demand Shocks: Swedish and Finnish Exporters By El-Sahli, Zouheir; Maczulskij, Terhi; Nilsson Hakkala, Katariina
  8. The Wage Effects of Employers' Associations: A Case Study of the Private Schools Sector By Martins, Pedro S.
  9. Fuzzy firm name matching: Merging Amadeus firm data to PATSTAT By Leon Bremer
  10. Firm Retention and Productivity of Apprentices By Jeremy Hervelin

  1. By: Stephanie Houle; Ryan Macdonald
    Abstract: Predicting which firms will grow quickly and why has been the subject of research studies for many decades. Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data. We apply a suite of supervised machine learning algorithms (elastic net model, random forest and neural net) to determine whether a large set of variables on Canadian firm tax filing financial and employment data, state variables (e.g., industry, geography) and indicators of firm complexity (e.g., multiple industrial activities, foreign ownership) can predict which firms will be high-growth firms over the next three years. The results suggest that the machine learning classifiers can select a sub-population of nascent high-growth firms that includes the majority of actual high-growth firms plus a group of firms that shared similar attributes but failed to attain high-growth status.
    Keywords: Econometric and statistical methods; Firm dynamics
    JEL: C55 C81 L25
    Date: 2023–10
  2. By: Huneeus, Federico; Larrain, Borja; Larrain, Mauricio; Prem, Mounu
    Abstract: We use matched employer-employee data together with data on the ownership networks of Chilean firms to document a novel relationship between inequality in labor income and ownership structures. Exploiting transitions of firms in and out of networks, we show that network affiliation is associated with higher inequality along two dimensions. First, network firms pay higher average wages than stand-alone firms, increasing between-firm inequality. Second, the dispersion of wages within a network firm is higher than within a stand-alone firm, increasing within-firm inequality. The effects are driven by increases in the wages of top workers, and by the entry of new top workers. Our findings shed light on the relationship between ownership structures and the distribution of labor income in the economy.
    Keywords: Earnings premium;Earnings inequality;Business groups;Ownership
    JEL: G32 J31
    Date: 2022–05
  3. By: Mary Amiti; Cédric Duprez; Jozef Konings; John Van Reenen
    Abstract: Numerous studies have documented the rising dominance of large firms over the last few decades in many industrialized countries. Many research papers have focused on the potential negative effects of this increased market concentration, raising concerns about market power in both labor and product markets. In a new study, we investigate whether large firms also generate positive effects. Our research shows that large firms generate significant positive total factor productivity (TFP) spillovers to their domestic suppliers. To date, these types of spillovers have only been identified for multinational enterprises located in developing countries. Using firm-to-firm transaction data for an industrialized country, Belgium, we find that large domestic firms, as well as multinationals, generate positive TFP spillovers.
    Keywords: large firms; productivity; spillovers
    JEL: E2
    Date: 2023–10–12
  4. By: Green, David A. (University of British Columbia, Vancouver); Liu, Huju (Statistics Canada); Ostrovsky, Yuri (Statistics Canada); Picot, Garnett (Institute for Research on Public Policy, and Research and Evaluation Branch, Immigration, Refugees and Citizenship Canada)
    Abstract: Firm ownership is a dening feature of immigrant adaptation: 41% of immigrants own a firm at some point in their first 10 years post-arrival. We use Canadian data linking immigrant arrival records with individual and firm tax data to examine the process of entering firm ownership for immigrants. Higher immigrant firm ownership rates are mainly due to nonincorporated firm ownership, which looks like a last resort. Human capital plays no role in the opening of preferable, incorporated firms. Immigrants are not more entrepreneurial in terms of opening incorporated firms with employees, and standard policy levers appear to have limited effects.
    Keywords: immigration, entrepreneurs, human capital
    JEL: J61
    Date: 2023–10
  5. By: Marta Arroyabe (University of Essex, UK); Katrin Hussinger (DEM, Université du Luxembourg)
    Abstract: The winner’s curse describes the behavioral phenomenon that the winner of a bidding contest pays a price which is too high. This paper shows that experiential learning cannot prevent a winner’s curse on the market of corporate control as acquiring firms with acquisition experience still pay a higher price for the target in a bidding contest. Acquisition experience, however, is related to a superior post-acquisition performance of the winning firm after acquisitions associated with a bidding contest.
    Keywords: Firm acquisitions, winner’s curse, bidding contest, acquisition experience, experiential learning.
    JEL: G34
    Date: 2023
  6. By: Samuel Bazzi; Marc-Andreas Muendler; Raquel F. Oliveira; James Rauch; James E. Rauch
    Abstract: We explore how financial constraints distort the entry decisions among otherwise productive entrepreneurs and limit growth of promising young firms. A model of liquidity-constrained entrepreneurs suggests that the easing of credit constraints can induce more entry of firms with greater long-run growth potential than the easing of conventional entry barriers would bring about. We explore this growth mechanism using a large-scale program to expand the supply of credit to small and medium enterprises in Brazil. Local credit supply shocks generate greater firm entry but also greater exit with no effect on short-run employment growth in the formal sector. However, credit expansions increase average capability among entering firms, which enter at larger size, survive longer, and grow faster. These firm dynamics are more pronounced in areas with weaker credit markets ex ante and consistent with local bank branches using cheap targeted credit lines to expand lending more broadly. Our findings provide new evidence on the general equilibrium effects of credit supply expansions.
    Keywords: credit constraints, entry barriers, growth barriers, startups
    JEL: D21 D22 D92 L25 L26 M13 O12
    Date: 2023
  7. By: El-Sahli, Zouheir; Maczulskij, Terhi; Nilsson Hakkala, Katariina
    Abstract: Abstract This paper analyzes how firms with different financial strength levels respond to demand shocks in their export markets. We utilize unique administrative datasets of Swedish and Finnish firms matched with national customs data from 1999 to 2014, which allows us to analyze the effects of several macroeconomic shocks affecting the export product demand and performance of exporting firms. We find that financially stronger export firms are better positioned during both positive and negative demand shocks—suffering less from the negative shocks, benefiting more from the positive shocks. While our results suggest that Swedish and Finnish firms tend to respond similarly to different export demand shocks, there are some salient differences in their survival strategies. While the financially stronger Swedish firms expanded their product lines and market areas, the Finnish firms did not make such adjustments during the 2007–2014 period of negative export demand shocks. By analyzing the firm-level survival strategies on export markets, we provide new insights into the divergent export growth trends of the two countries.
    Keywords: Export competition, Financial strength, Firm-level, Trade flows
    JEL: F14 F61 L11 L25 D22
    Date: 2023–10–16
  8. By: Martins, Pedro S. (Nova School of Business and Economics)
    Abstract: Does employers' association (EA) membership affect wages? Such effects, positive or negative, could follow from increased productivity, employer collusion, or other channels. We analyse this question drawing on matched employer-employee panel data, including time-varying EA affiliation and worker mobility. We consider the case of private schools in Portugal, 2010-2020, and its single EA, and develop a method to define the sector's scope. We find that school fixed effects reduce the EA wage premium considerably. However, such positive premium remains, especially when focusing on the key occupation of the industry (teachers) and when considering EA firms that follow firm-specific (non-EA) collective agreements. We also find that there is an EA wage premium for schools that join the EA, while the EA premium does not disappear for schools that leave the EA.
    Keywords: employers organisations, worker mobility, social dialogue
    JEL: J53 J62 L40
    Date: 2023–09
  9. By: Leon Bremer (Vrije Universiteit Amsterdam)
    Abstract: When merging firms across large databases in the absence of common identifiers, text algorithms can help. I propose a high-performance fuzzy firm name matching algorithm that uses existing computational methods and works even under hardware restrictions. The algorithm consists of four steps, namely (1) cleaning, (2) similarity scoring, (3) a decision rule based on supervised machine learning, and (4) group identification using community detection. The algorithm is applied to merging firms in the Amadeus Financials and Subsidiaries databases, containing firm-level business and ownership information, to applicants in PATSTAT, a worldwide patent database. For the application the algorithm vastly outperforms an exact string match by increasing the number of matched firms in the Amadeus Financials (Subsidiaries) database with 116% (160%). 53% (74%) of this improvement is due to cleaning, and another 41% (50%) improvement is due to similarity matching. 18.1% of all patent applications since 1950 are matched to firms in the Amadeus databases, compared to 2.6% for an exact name match.
    Keywords: Fuzzy name matching, supervised machine learning, name disambiguation, patents
    JEL: C81 C88 O34
    Date: 2023–10–12
  10. By: Jeremy Hervelin (Université de Cergy-Pontoise, THEMA)
    Abstract: This study investigates the retention rate of young people in firms that offer apprenticeship positions. While the majority of training firms hire apprentices with the aim of retaining them when the contract ends, only a small proportion of youths actually transition into full-time employment in the same firm. To explain this phenomenon, I rely on a tractable model that incorporates firm decision-making processes, enabling an analysis of the retention rate. By estimating the productivity distribution of apprentices based on observed wage data from French surveys, the findings indicate that training firms, on average, benefit more from separating from apprentices rather than hiring them as workers.
    Keywords: Firm retention, Productivity, Apprenticeship, Maximum Likelihood
    JEL: J24 M53 M51
    Date: 2023

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