scholarly journals Large Firm Dynamics and the Business Cycle

2019 ◽  
Vol 109 (4) ◽  
pp. 1375-1425 ◽  
Author(s):  
Vasco M. Carvalho ◽  
Basile Grassi
Keyword(s):  
Business Cycle ◽  
Size Distribution ◽  
Firm Size ◽  
Large Firm ◽  
Firm Dynamics ◽  
Aggregate Fluctuations ◽  
Firm Level ◽  
Firm Size Distribution ◽  
The Business Cycle

Do large firm dynamics drive the business cycle? We answer this question by developing a quantitative theory of aggregate fluctuations caused by firm-level disturbances alone. We show that a standard heterogeneous firm dynamics setup already contains in it a theory of the business cycle, without appealing to aggregate shocks. We offer an analytical characterization of the law of motion of the aggregate state in this class of models, the firm size distribution, and show that aggregate output and productivity dynamics display: (i ) persistence, (ii ) volatility, and (iii ) time-varying second moments. We explore the key role of moments of the firm size distribution, and, in particular, the role of large firm dynamics, in shaping aggregate fluctuations, theoretically, quantitatively, and in the data. (JEL D21, D22, D24, E32, L11)

scholarly journals Big Data and Firm Dynamics

2019 ◽  
Vol 109 ◽  
pp. 38-42 ◽  
Author(s):  
Maryam Farboodi ◽  
Roxana Mihet ◽  
Thomas Philippon ◽  
Laura Veldkamp
Keyword(s):  
Big Data ◽  
Size Distribution ◽  
Firm Size ◽  
Firm Dynamics ◽  
Social Value ◽  
The Other ◽  
Intangible Asset ◽  
Small Data ◽  
Firm Size Distribution ◽  
Asset Data

We study a model where firms accumulate data as a valuable intangible asset. Data accumulation affects firms' dynamics. It increases the skewness of the firm size distribution as large firms generate more data and invest more in active experimentation. On the other hand, small data-savvy firms can overtake more traditional incumbents, provided they can finance their initial money-losing growth. Our model can be used to estimate the market and social value of data.

scholarly journals Lessons from Schumpeterian Growth Theory

2015 ◽  
Vol 105 (5) ◽  
pp. 94-99 ◽  
Author(s):  
Philippe Aghion ◽  
Ufuk Akcigit ◽  
Peter Howitt
Keyword(s):  
Industrial Organization ◽  
Size Distribution ◽  
Firm Size ◽  
Growth Process ◽  
Firm Dynamics ◽  
Growth Theory ◽  
Micro Data ◽  
Firm Size Distribution ◽  
Schumpeterian Growth ◽  
Schumpeterian Growth Theory

By operationalizing the notion of creative destruction, Schumpeterian growth theory generates distinctive predictions on important microeconomic aspects of the growth process (competition, firm dynamics, firm size distribution, cross-firm and cross-sector reallocation) which can be confronted using rich micro data. In this process the theory helps reconcile growth with industrial organization and development economics.

scholarly journals THE DYNAMICS OF MANUFACTURING INDUSTRY AND THE RESPONSE TOWARD BUSINESS CYCLE

2010 ◽  
Vol 13 (2) ◽  
pp. 131-164
Author(s):  
Yati Kurniati ◽  
Yanfitri Yanfitri
Keyword(s):  
Business Cycle ◽  
Production Cost ◽  
Manufacturing Industry ◽  
Firm Level ◽  
Industry Studies ◽  
Business Fluctuations ◽  
Productivity Rate ◽  
The Business Cycle ◽  
Boom Period

The role of the manufacturing industry in the economy has expanded significantly from 19 percent in 1990 to 26 percent in 2009, while its labor absorption only increased from 10 percent to 12.2 percent. The cycle of the manufacturing industry has been in line with the economic growth. This study explores the implications of the firm-level heterogeneity over the business cycle. By using the panel multinomial logit, it shows that firms with less capital and small size have greater probability to exit the industry during the boom/ bust period. Sensitivity of the company to changes in capital is greater during the boom period. Only highly productive firms enter and begin production during recessions. Companies with higher productivity rate also have greater probability to enter the market. In contrast, higher production cost and higher market concentration increase the probability for smaller companies to exit from the industry.JEL Classification:  : D24, L6, E32Keywords: Production, Cost, Capital and Total Factor Productivity, Industry Studies Manufacturing, Business Fluctuations/cycles

scholarly journals Small and Large Firms over the Business Cycle

2020 ◽  
Vol 110 (11) ◽  
pp. 3549-3601
Author(s):  
Nicolas Crouzet ◽  
Neil R. Mehrotra
Keyword(s):  
Business Cycle ◽  
Firm Size ◽  
Census Data ◽  
Financial Frictions ◽  
Alternative Mechanism ◽  
Large Firms ◽  
Aggregate Fluctuations ◽  
Financial Strength ◽  
The Business Cycle ◽  
The Relationship

This paper uses new confidential Census data to revisit the relationship between firm size, cyclicality, and financial frictions. First, we find that large firms (the top 1 percent by size) are less cyclically sensitive than the rest. Second, high and rising concentration implies that the higher cyclicality of the bottom 99 percent of firms only has a modest impact on aggregate fluctuations. Third, differences in cyclicality are not simply explained by financing, and in fact appear largely unrelated to proxies for financial strength. We instead provide evidence for an alternative mechanism based on the industry scope of the very largest firms. (JEL D22, E32, G32, L25)

The Nature of Firm Growth

2021 ◽  
Vol 111 (2) ◽  
pp. 547-579
Author(s):  
Vincent Sterk ◽  
Petr Sedláček ◽  
Benjamin Pugsley
Keyword(s):  
Firm Size ◽  
Firm Growth ◽  
High Growth ◽  
Firm Dynamics ◽  
Dynamics Model ◽  
Firm Level ◽  
Firm Size Distribution ◽  
Ex Post ◽  
Ex Ante ◽  
Macroeconomic Effects

About one-half of all startups fail within five years, and those that survive grow at vastly different speeds. Using Census microdata, we estimate that most of these differences are determined by ex ante heterogeneity rather than persistent ex post shocks. Embedding such heterogeneity in a firm dynamics model shows that the presence of ex ante heterogeneity (i) is a key determinant of the firm size distribution and firm dynamics, (ii) can strongly affect the macroeconomic effects of firm-level frictions, and (iii) helps understand the recently documented decline in business dynamism by showing a disappearance of high-growth startups (“gazelles”) since the mid-1980s. (JEL D22, D24, E24, J23, L11, M13)

Employers and the 1881 Population Census of England and Wales

2015 ◽  
pp. 29-49 ◽  
Author(s):  
Robert J. Bennett ◽  
Gill Newton
Keyword(s):  
Systematic Error ◽  
Size Distribution ◽  
Firm Size ◽  
Extraction Method ◽  
Building Industry ◽  
Population Census ◽  
Firm Size Distribution ◽  
England And Wales ◽  
Occupational Information ◽  
First Results

This article presents the method and first results of using the 1881 England and Wales Census Enumerators' Books (CEBs) to identify and extract employer records using occupational information. Over 230,000 employers are identified, of which about four fifths employ others. Important sub-groups are also identified of the own account selfemployed, company proprietors, directors and partnerships. The article demonstrates the feasibility of the method and uses the example of the building industry to illustrate firm-size distribution at parish level across England and Wales. The paper indicates the applicability of the extraction method to other censuses, which is now possible using the recently released I-CeM database. The paper also demonstrates some difficulties in the database for 1881, including data keying and coding errors, ranging from 0.5 to 5.5 per cent of entries for larger businesses. Gender miscoding appears to be a systematic error of about 0.7 per 1,000 people. The analysis suggests that where small or atypical sample groups are involved, users of the census database should make detailed checks with manuscript CEBs.

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