Interregional Migration and Implications for Regional Resilience View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-05-01

AUTHORS

Daniel Crown , Timothy Jaquet , Alessandra Faggian

ABSTRACT

Regional resilience is a growing topic that encompasses many ideas, including what factors reduce the impact of negative shocks, or enhance a region’s ability to recover or adapt. In this chapter we examine the relationship between patterns of migration during periods of recession and the overall economic resilience of an area. Determining whether the characteristics that attract migrants also contribute to an area’s resilience is an important question to policymakers who seek to improve their local area’s resilience to economic shocks. Our principal finding is that during an economic downturn migrants are less likely to move to an area with a different industrial composition than that of their origin county. We interpret this finding as evidence that migrants face frictions which prevent them from moving to counties with relatively high performing industries and instead respond to economic shocks by moving to a county with the same industrial sectors, but that may have been less-affected by the recession. When we examine the factors which contribute to the economic resilience of an area, we find that the characteristics which contribute to resilience during a recession are different than those that are significant in other periods. Specifically, during a recession, the role of a county’s industrial structure is the primary factor that contributes to the resilience of an area. Together, these findings imply that a county’s industrial composition is a driving force behind both migration during a recession and the economic resilience of an area. More... »

PAGES

231-252

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-75886-2_11

DOI

http://dx.doi.org/10.1007/978-3-319-75886-2_11

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1103690624


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/14", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Economics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1402", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Applied Economics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Agricultural, Environmental, and Development Economics, The Ohio State University, Columbus, OH, USA", 
          "id": "http://www.grid.ac/institutes/grid.261331.4", 
          "name": [
            "Department of Agricultural, Environmental, and Development Economics, The Ohio State University, Columbus, OH, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Crown", 
        "givenName": "Daniel", 
        "id": "sg:person.014505344632.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014505344632.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Agricultural, Environmental, and Development Economics, The Ohio State University, Columbus, OH, USA", 
          "id": "http://www.grid.ac/institutes/grid.261331.4", 
          "name": [
            "Department of Agricultural, Environmental, and Development Economics, The Ohio State University, Columbus, OH, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jaquet", 
        "givenName": "Timothy", 
        "id": "sg:person.015353732427.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015353732427.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Social Sciences, Gran Sasso Science Institute, L\u2019Aquila, Italy", 
          "id": "http://www.grid.ac/institutes/grid.466750.6", 
          "name": [
            "Social Sciences, Gran Sasso Science Institute, L\u2019Aquila, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Faggian", 
        "givenName": "Alessandra", 
        "id": "sg:person.010451017403.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010451017403.70"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2018-05-01", 
    "datePublishedReg": "2018-05-01", 
    "description": "Regional resilience is a growing topic that encompasses many ideas, including what factors reduce the impact of negative shocks, or enhance a region\u2019s ability to recover or adapt. In this chapter we examine the relationship between patterns of migration during periods of recession and the overall economic resilience of an area. Determining whether the characteristics that attract migrants also contribute to an area\u2019s resilience is an important question to policymakers who seek to improve their local area\u2019s resilience to economic shocks. Our principal finding is that during an economic downturn migrants are less likely to move to an area with a different industrial composition than that of their origin county. We interpret this finding as evidence that migrants face frictions which prevent them from moving to counties with relatively high performing industries and instead respond to economic shocks by moving to a county with the same industrial sectors, but that may have been less-affected by the recession. When we examine the factors which contribute to the economic resilience of an area, we find that the characteristics which contribute to resilience during a recession are different than those that are significant in other periods. Specifically, during a recession, the role of a county\u2019s industrial structure is the primary factor that contributes to the resilience of an area. Together, these findings imply that a county\u2019s industrial composition is a driving force behind both migration during a recession and the economic resilience of an area.", 
    "editor": [
      {
        "familyName": "Biagi", 
        "givenName": "Bianca", 
        "type": "Person"
      }, 
      {
        "familyName": "Faggian", 
        "givenName": "Alessandra", 
        "type": "Person"
      }, 
      {
        "familyName": "Rajbhandari", 
        "givenName": "Isha", 
        "type": "Person"
      }, 
      {
        "familyName": "Venhorst", 
        "givenName": "Viktor A.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-75886-2_11", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-75885-5", 
        "978-3-319-75886-2"
      ], 
      "name": "New Frontiers in Interregional Migration Research", 
      "type": "Book"
    }, 
    "keywords": [
      "economic resilience", 
      "industrial composition", 
      "economic shocks", 
      "regional resilience", 
      "industrial structure", 
      "area resilience", 
      "periods of recession", 
      "same industrial sector", 
      "negative shocks", 
      "interregional migration", 
      "origin counties", 
      "region's ability", 
      "recession", 
      "industrial sectors", 
      "shock", 
      "patterns of migration", 
      "migrants", 
      "principal findings", 
      "important questions", 
      "policymakers", 
      "sector", 
      "County", 
      "resilience", 
      "industry", 
      "primary factor", 
      "impact", 
      "implications", 
      "period", 
      "findings", 
      "evidence", 
      "chapter", 
      "questions", 
      "friction", 
      "factors", 
      "migration", 
      "relationship", 
      "area", 
      "topic", 
      "characteristics", 
      "idea", 
      "force", 
      "role", 
      "ability", 
      "patterns", 
      "structure", 
      "composition", 
      "overall economic resilience", 
      "local area\u2019s resilience", 
      "economic downturn migrants", 
      "downturn migrants", 
      "different industrial composition", 
      "high performing industries", 
      "performing industries", 
      "county\u2019s industrial structure", 
      "county\u2019s industrial composition"
    ], 
    "name": "Interregional Migration and Implications for Regional Resilience", 
    "pagination": "231-252", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1103690624"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-75886-2_11"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-75886-2_11", 
      "https://app.dimensions.ai/details/publication/pub.1103690624"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2021-11-01T19:04", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211101/entities/gbq_results/chapter/chapter_94.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-319-75886-2_11"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75886-2_11'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75886-2_11'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75886-2_11'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75886-2_11'


 

This table displays all metadata directly associated to this object as RDF triples.

147 TRIPLES      23 PREDICATES      79 URIs      72 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-75886-2_11 schema:about anzsrc-for:14
2 anzsrc-for:1402
3 schema:author Nb00b11a9321846d3805bc7b8b0769c25
4 schema:datePublished 2018-05-01
5 schema:datePublishedReg 2018-05-01
6 schema:description Regional resilience is a growing topic that encompasses many ideas, including what factors reduce the impact of negative shocks, or enhance a region’s ability to recover or adapt. In this chapter we examine the relationship between patterns of migration during periods of recession and the overall economic resilience of an area. Determining whether the characteristics that attract migrants also contribute to an area’s resilience is an important question to policymakers who seek to improve their local area’s resilience to economic shocks. Our principal finding is that during an economic downturn migrants are less likely to move to an area with a different industrial composition than that of their origin county. We interpret this finding as evidence that migrants face frictions which prevent them from moving to counties with relatively high performing industries and instead respond to economic shocks by moving to a county with the same industrial sectors, but that may have been less-affected by the recession. When we examine the factors which contribute to the economic resilience of an area, we find that the characteristics which contribute to resilience during a recession are different than those that are significant in other periods. Specifically, during a recession, the role of a county’s industrial structure is the primary factor that contributes to the resilience of an area. Together, these findings imply that a county’s industrial composition is a driving force behind both migration during a recession and the economic resilience of an area.
7 schema:editor N76911b65bf8c42029bf5c3f591990b23
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf Ne15abb570d9e47d1afcfb4758e9e18ab
12 schema:keywords County
13 ability
14 area
15 area resilience
16 chapter
17 characteristics
18 composition
19 county’s industrial composition
20 county’s industrial structure
21 different industrial composition
22 downturn migrants
23 economic downturn migrants
24 economic resilience
25 economic shocks
26 evidence
27 factors
28 findings
29 force
30 friction
31 high performing industries
32 idea
33 impact
34 implications
35 important questions
36 industrial composition
37 industrial sectors
38 industrial structure
39 industry
40 interregional migration
41 local area’s resilience
42 migrants
43 migration
44 negative shocks
45 origin counties
46 overall economic resilience
47 patterns
48 patterns of migration
49 performing industries
50 period
51 periods of recession
52 policymakers
53 primary factor
54 principal findings
55 questions
56 recession
57 region's ability
58 regional resilience
59 relationship
60 resilience
61 role
62 same industrial sector
63 sector
64 shock
65 structure
66 topic
67 schema:name Interregional Migration and Implications for Regional Resilience
68 schema:pagination 231-252
69 schema:productId N19cca82feb8c47cc9ce281f4d8a0223b
70 Naf7337bc0af741d59097dc5c68f48a71
71 schema:publisher N35b60587c3234c8d867dd63f6c1873ae
72 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103690624
73 https://doi.org/10.1007/978-3-319-75886-2_11
74 schema:sdDatePublished 2021-11-01T19:04
75 schema:sdLicense https://scigraph.springernature.com/explorer/license/
76 schema:sdPublisher N2f917bca338e4150a5fe7ef2f8cb511b
77 schema:url https://doi.org/10.1007/978-3-319-75886-2_11
78 sgo:license sg:explorer/license/
79 sgo:sdDataset chapters
80 rdf:type schema:Chapter
81 N013c4ddc576947e28818d1611f155325 schema:familyName Rajbhandari
82 schema:givenName Isha
83 rdf:type schema:Person
84 N19cca82feb8c47cc9ce281f4d8a0223b schema:name dimensions_id
85 schema:value pub.1103690624
86 rdf:type schema:PropertyValue
87 N2f917bca338e4150a5fe7ef2f8cb511b schema:name Springer Nature - SN SciGraph project
88 rdf:type schema:Organization
89 N35b60587c3234c8d867dd63f6c1873ae schema:name Springer Nature
90 rdf:type schema:Organisation
91 N3b9ecfef2231406f8c21b02dcce4784c rdf:first N4d17431dfcde4ca5b9b627e3ed1ab488
92 rdf:rest Nd7dcc69deaa744baa133412fccb2b990
93 N4d17431dfcde4ca5b9b627e3ed1ab488 schema:familyName Faggian
94 schema:givenName Alessandra
95 rdf:type schema:Person
96 N76911b65bf8c42029bf5c3f591990b23 rdf:first Nde30106e9ed341dfab3afe96c0a48e4f
97 rdf:rest N3b9ecfef2231406f8c21b02dcce4784c
98 N9bbcb4215be34203a8fd9a27dcb01d1f rdf:first sg:person.010451017403.70
99 rdf:rest rdf:nil
100 Naf7337bc0af741d59097dc5c68f48a71 schema:name doi
101 schema:value 10.1007/978-3-319-75886-2_11
102 rdf:type schema:PropertyValue
103 Nb00b11a9321846d3805bc7b8b0769c25 rdf:first sg:person.014505344632.40
104 rdf:rest Nbfbf5387021247ac8b88cfe187eaaf2a
105 Nbfbf5387021247ac8b88cfe187eaaf2a rdf:first sg:person.015353732427.27
106 rdf:rest N9bbcb4215be34203a8fd9a27dcb01d1f
107 Ncee1719d35f843149d247c85468107d1 rdf:first Nfc9b1b338ef943b78ef760fb0f04b3ee
108 rdf:rest rdf:nil
109 Nd7dcc69deaa744baa133412fccb2b990 rdf:first N013c4ddc576947e28818d1611f155325
110 rdf:rest Ncee1719d35f843149d247c85468107d1
111 Nde30106e9ed341dfab3afe96c0a48e4f schema:familyName Biagi
112 schema:givenName Bianca
113 rdf:type schema:Person
114 Ne15abb570d9e47d1afcfb4758e9e18ab schema:isbn 978-3-319-75885-5
115 978-3-319-75886-2
116 schema:name New Frontiers in Interregional Migration Research
117 rdf:type schema:Book
118 Nfc9b1b338ef943b78ef760fb0f04b3ee schema:familyName Venhorst
119 schema:givenName Viktor A.
120 rdf:type schema:Person
121 anzsrc-for:14 schema:inDefinedTermSet anzsrc-for:
122 schema:name Economics
123 rdf:type schema:DefinedTerm
124 anzsrc-for:1402 schema:inDefinedTermSet anzsrc-for:
125 schema:name Applied Economics
126 rdf:type schema:DefinedTerm
127 sg:person.010451017403.70 schema:affiliation grid-institutes:grid.466750.6
128 schema:familyName Faggian
129 schema:givenName Alessandra
130 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010451017403.70
131 rdf:type schema:Person
132 sg:person.014505344632.40 schema:affiliation grid-institutes:grid.261331.4
133 schema:familyName Crown
134 schema:givenName Daniel
135 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014505344632.40
136 rdf:type schema:Person
137 sg:person.015353732427.27 schema:affiliation grid-institutes:grid.261331.4
138 schema:familyName Jaquet
139 schema:givenName Timothy
140 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015353732427.27
141 rdf:type schema:Person
142 grid-institutes:grid.261331.4 schema:alternateName Department of Agricultural, Environmental, and Development Economics, The Ohio State University, Columbus, OH, USA
143 schema:name Department of Agricultural, Environmental, and Development Economics, The Ohio State University, Columbus, OH, USA
144 rdf:type schema:Organization
145 grid-institutes:grid.466750.6 schema:alternateName Social Sciences, Gran Sasso Science Institute, L’Aquila, Italy
146 schema:name Social Sciences, Gran Sasso Science Institute, L’Aquila, Italy
147 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...