Labor mobility and industrial space in Argentina

Sergio Andrés De Raco; Viktoriya Semeshenko

doi:10.3934/jdg.2019008

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2019, Volume 6, Issue 2: 107-118. Doi: 10.3934/jdg.2019008

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Labor mobility and industrial space in Argentina

Sergio Andrés De Raco^1, and
Viktoriya Semeshenko^2, ,

1.
Instituto Interdisciplinario de Economía Política (IIEP-BAIRES), University of Buenos Aires, Buenos Aires, Argentina
2.
Instituto Interdisciplinario de Economía Política (IIEP-BAIRES), UBA-CONICET, Buenos Aires, Argentina

^* Corresponding author: Viktoriya Semeshenko
^* Corresponding author: Viktoriya Semeshenko

Received: December 2018

Revised: March 2019

Published: April 2019

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Abstract

In this paper, we apply the skill-relatedness (SR) indicator measure for the analysis of labor flow dynamics in Argentina, and compare it with the original flows in order to differentiate the type of information that each of these techniques offers for characterizing the productive system based on the dynamics of private formal employment. On the other hand, given the size and complexity of the obtained networks, it is interesting to explore the biases introduced by different methods of network reduction in the derived structures as well as to characterize the obtained industrial spaces.

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Mathematics Subject Classification: Primary: 91B40, 68R10; Secondary: 90B10.

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Figure 1. Network of Flows: Structural aspects of the inter-industrial flows graph of average formal employment 2009-2014. (a) Graph obtained with Fruchterman-Reingold layout. (b) Distribution of the average employment endowment by sectors and activity sections. (c) Distribution of interindustrial flows (weights, strength). (d) Distribution of distances of the unweighted graph

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Figure 2. Structural aspects of the directed flow graph based on models. (a) A center-periphery structure is observed, with few sectors highly interconnected with each other and with the others (center), other two groups with less interaction with each other although with characteristics similar to the center, and a last group with little interaction between them and greater interaction with the rest of the sectors (periphery). (b) The distribution of the weighted graph of original flows presented a very different distribution to that generated by the preferential attachment model (Barabási-Albert) with the parameters of the graph depicted in (c), more similar to a distribution of normal multimodal mixtures than a power law

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Figure 3. Reduction of the original flow network. (a) Logarithmic relationship between flows and edges according to the selected thresholds. (b) Graph obtained with Fruchterman-Reingold layout for the restriction of 5 or more individuals. A structure was observed by specific activity sections located in concentrated regions and in some cases (predominantly services and industry) distributed in the graph

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Figure 4. Industrial space and reduction of skill-relatedness network. (a) Heatmap of the normalized and symmetrized SR matrix ordered by hierarchical clustering with complete linkage criterion. (b) Graph of the industrial space obtained with the Fruchterman-Reingold layout for the expanded MST with 3*number of nodes, according to Neffke et al [6]

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Table 1. Broad Structure of Economic activities (ISIC Rev 4, UNSD)

Section	Divisions	Description
A	01-03	Agriculture, forestry and fishing
B	05-09	Mining and quarrying
C	10-33	Manufacturing
D	35	Electricity, gas, steam and air conditioning supply
E	36-39	Water supply; sewerage, waste management and remediation activities
F	41-43	Construction
G	45-47	Wholesale and retail trade; repair of motor vehicles and motorcycles
H	49-53	Transportation and storage
I	55-56	Accommodation and food service activities
J	58-63	Information and communication
K	64-66	Financial and insurance activities
L	68	Real estate activities
M	69-75	Professional, scientific and technical activities
N	77-82	Administrative and support service activities
O	84	Public administration and defence; compulsory social security
P	85	Education
Q	86-88	Human health and social work activities
R	90-93	Arts, entertainment and recreation
S	94-96	Other service activities
T	97-98	Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use
U	99	Activities of extraterritorial organizations and bodies

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Table 2. Average employment and cross-industry labor flows: In relative terms with respect to average employment, the proportion of inter-industry flows in Germany is greater than in the case of Argentina, possibly due to the greater level of sectoral detail (5-digits), and hence the total number of nodes in the network. However, the proportion of inter-industry flows that cross the section level (letter) is similar (58.7% vs 58%)

Workers (thousands)	Germany 1999-2008	Argentina 2009-2014
Workers (thousands)	NACE Rev 1.1 5-digits	ISIC Rev 4 4-digits
Stock:
Employment	19897.1	5619.1
Absolute flows:
Job Switchers	1206.7	412.1
No Industry Switch	321.1	206.1
Industry Switch	885.7	206
Different Sector	519.8	119.4
Same Sector	365.9	86.6
Same 2-Digit Industry	225.9	37.1
Same 3-Digit Industry	117.3	14.6
Same 4-Digit Industry	62.3	n.a.
Relative flows (w.r.t. total average employment):
Job Switchers	6.1%	7.3%
No Industry Switch	26.6%	50.0%
Industry Switch	73.4%	50.0%
Different Sector	58.7%	58.0%
Same Sector	41.3%	42.0%
Same 2-Digit Industry	25.5%	18.0%
Same 3-Digit Industry	13.2%	7.1%
Same 4-Digit Industry	7.0%	n.a.

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[1]	F. Bertranou and L. Casanova, Informalidad Laboral en Argentina: Segmentos Críticos y Políticas Para la Formalización, Organización Internacional del Trabajo, 2013.
[2]	G. Csardi and T. Nepusz, The igraph software package for complex networks research, InterJournal, Complex Systems, (1965), http://igraph.org
[3]	S. De Raco and L. Tumini, Parentesco de habilidades y nuevos sectores económicos. Un análisis exploratorio para la Argentina, Documento de Trabajo MTEYSS-OIT, 2018.
[4]	C. Hidalgo and R. Hausmann, The building blocks of economic complexity, Proceedings of the National Academy of Science, 106 (2009), 10570–10575, https://doi.org/10.1073/pnas.0900943106. doi: 10.1073/pnas.0900943106.
[5]	F. Neffke and M. Henning, Skill-relatedness and Firm diversification, Strategic Management Journal, 34 (2013), 297-316. doi: 10.1002/smj.2014.
[6]	F. Neffke, A. Otto and A. Weyh, Inter-industry labor flows, Journal of Economic Behavior & Organization, 142 (2017), 275-292. doi: 10.1016/j.jebo.2017.07.003.
[7]	F. Neffke, A. Otto and A. Weyh, Skill-relatedness Matrices for Germany: Data Method and Access, FDZ Methodenreport 201704_en. Institutfur Arbeitsmarkt- und Berufsforschung (IAB), Nurnberg.
[8]	R. C. Prim, Shortest connection networks and some generalizations, Bell System Technical Journal, 36 (1957), 1389-1401. doi: 10.1002/j.1538-7305.1957.tb01515.x.

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