Does globalization exacerbate income inequality in two largest emerging economies? The role of FDI and remittances inflows View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2020-05-12

AUTHORS

Hrushikesh Mallick, Mantu Kumar Mahalik, Hemachandra Padhan

ABSTRACT

Using the annual data from 1980 to 2013, this study explores the effects of economic globalization on income inequality for a sample of two emerging economics, China and India, by endogenizing FDI inflows, remittances inflows, sectoral output, infrastructural development, human capital formation, government size, urbanization and economic growth as relevant determinants into the income inequality model. By applying combined cointegration method of Bayer–Hanck (J Time Ser Anal 34(1): 83–95, 2013) and ARDL bounds testing of cointegration approach of Pesaran et al. (J Appl Econom 16(3):289–326, 2001); it finds that there is the existence of a long-run relationship among the variables in our inequality model for both India and China. After confirming cointegration among the variables, the long-run results based on ARDL model surprisingly revealed that economic globalization widens the income inequality in India but the same factor reduces the income inequality in China. Contrastingly, both the FDI and remittances inflows significantly contribute to reduce income inequality in China, while the same worsens the income inequality in India. In examining the role and effects of structural changes in both the economies from the changing sectoral contributions of output in total output (industry sector and service sectors) in our model, it exposes the fact that the changing sectoral growth contribution has been leading to rising income inequality in China while the same has been resulting in reduction of income inequality in India. The infrastructural development has led to rising income inequality in both the countries, while human capital formation as expected reduces income inequality for both the countries. It also observes that economic growth, urbanization and government size enable both the economies to improve in their pattern of income distribution which have significant implication for public policy of both the economies while aiming at reducing poverty and inequality. More... »

PAGES

443-480

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12232-020-00350-0

DOI

http://dx.doi.org/10.1007/s12232-020-00350-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1127546142


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"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1403", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Econometrics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Centre for Development Studies, Trivandrum, Kerala, India", 
          "id": "http://www.grid.ac/institutes/grid.433028.e", 
          "name": [
            "Centre for Development Studies, Trivandrum, Kerala, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mallick", 
        "givenName": "Hrushikesh", 
        "id": "sg:person.015046426225.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015046426225.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, Medinipur, West Bengal, India", 
          "id": "http://www.grid.ac/institutes/grid.429017.9", 
          "name": [
            "Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, Medinipur, West Bengal, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mahalik", 
        "givenName": "Mantu Kumar", 
        "id": "sg:person.07747377034.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07747377034.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Humanities and Social Sciences, Indian Institute of Technology, Madras, Chennai, Tamil Nadu, India", 
          "id": "http://www.grid.ac/institutes/grid.417969.4", 
          "name": [
            "Department of Humanities and Social Sciences, Indian Institute of Technology, Madras, Chennai, Tamil Nadu, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Padhan", 
        "givenName": "Hemachandra", 
        "id": "sg:person.010002330534.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010002330534.20"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1057/imfer.2013.7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051945227", 
          "https://doi.org/10.1057/imfer.2013.7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02298327", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026589275", 
          "https://doi.org/10.1007/bf02298327"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02707386", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001716375", 
          "https://doi.org/10.1007/bf02707386"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11205-016-1229-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049168704", 
          "https://doi.org/10.1007/s11205-016-1229-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1009850119329", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018247772", 
          "https://doi.org/10.1023/a:1009850119329"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00138861", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053705392", 
          "https://doi.org/10.1007/bf00138861"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2020-05-12", 
    "datePublishedReg": "2020-05-12", 
    "description": "Using the annual data from 1980 to 2013, this study explores the effects of economic globalization on income inequality for a sample of two emerging economics, China and India, by endogenizing FDI inflows, remittances inflows, sectoral output, infrastructural development, human capital formation, government size, urbanization and economic growth as relevant determinants into the income inequality model. By applying combined cointegration method of Bayer\u2013Hanck (J Time Ser Anal 34(1): 83\u201395, 2013) and ARDL bounds testing of cointegration approach of Pesaran et al. (J Appl Econom 16(3):289\u2013326, 2001); it finds that there is the existence of a long-run relationship among the variables in our inequality model for both India and China. After confirming cointegration among the variables, the long-run results based on ARDL model surprisingly revealed that economic globalization widens the income inequality in India but the same factor reduces the income inequality in China. Contrastingly, both the FDI and remittances inflows significantly contribute to reduce income inequality in China, while the same worsens the income inequality in India. In examining the role and effects of structural changes in both the economies from the changing sectoral contributions of output in total output (industry sector and service sectors) in our model, it exposes the fact that the changing sectoral growth contribution has been leading to rising income inequality in China while the same has been resulting in reduction of income inequality in India. The infrastructural development has led to rising income inequality in both the countries, while human capital formation as expected reduces income inequality for both the countries. It also observes that economic growth, urbanization and government size enable both the economies to improve in their pattern of income distribution which have significant implication for public policy of both the economies while aiming at reducing poverty and inequality.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s12232-020-00350-0", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1412840", 
        "issn": [
          "1865-1704", 
          "1863-4613"
        ], 
        "name": "International Review of Economics", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "67"
      }
    ], 
    "keywords": [
      "income inequality", 
      "human capital formation", 
      "government size", 
      "capital formation", 
      "economic growth", 
      "economic globalization", 
      "inequality model", 
      "ARDL bounds testing", 
      "Pesaran et al", 
      "role of FDI", 
      "infrastructural development", 
      "Bayer\u2013Hanck", 
      "run relationship", 
      "FDI inflows", 
      "sectoral output", 
      "cointegration approach", 
      "ARDL model", 
      "income distribution", 
      "cointegration method", 
      "bounds testing", 
      "annual data", 
      "run results", 
      "growth contribution", 
      "sectoral contributions", 
      "total output", 
      "relevant determinants", 
      "economy", 
      "public policy", 
      "inequality", 
      "FDI", 
      "inflow", 
      "globalization", 
      "countries", 
      "China", 
      "structural changes", 
      "India", 
      "cointegration", 
      "economics", 
      "significant implications", 
      "urbanization", 
      "output", 
      "poverty", 
      "policy", 
      "same factors", 
      "growth", 
      "variables", 
      "determinants", 
      "model", 
      "implications", 
      "et al", 
      "contribution", 
      "development", 
      "fact", 
      "existence", 
      "relationship", 
      "effect", 
      "role", 
      "data", 
      "size", 
      "approach", 
      "changes", 
      "factors", 
      "distribution", 
      "results", 
      "reduction", 
      "patterns", 
      "al", 
      "study", 
      "samples", 
      "method", 
      "formation", 
      "testing"
    ], 
    "name": "Does globalization exacerbate income inequality in two largest emerging economies? The role of FDI and remittances inflows", 
    "pagination": "443-480", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1127546142"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12232-020-00350-0"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12232-020-00350-0", 
      "https://app.dimensions.ai/details/publication/pub.1127546142"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-05-20T07:36", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/article/article_844.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s12232-020-00350-0"
  }
]
 

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/s12232-020-00350-0'

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/s12232-020-00350-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12232-020-00350-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12232-020-00350-0'


 

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

178 TRIPLES      22 PREDICATES      104 URIs      89 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12232-020-00350-0 schema:about anzsrc-for:14
2 anzsrc-for:1402
3 anzsrc-for:1403
4 schema:author Ndcfce17e10714d4798c2ad3428873658
5 schema:citation sg:pub.10.1007/bf00138861
6 sg:pub.10.1007/bf02298327
7 sg:pub.10.1007/bf02707386
8 sg:pub.10.1007/s11205-016-1229-1
9 sg:pub.10.1023/a:1009850119329
10 sg:pub.10.1057/imfer.2013.7
11 schema:datePublished 2020-05-12
12 schema:datePublishedReg 2020-05-12
13 schema:description Using the annual data from 1980 to 2013, this study explores the effects of economic globalization on income inequality for a sample of two emerging economics, China and India, by endogenizing FDI inflows, remittances inflows, sectoral output, infrastructural development, human capital formation, government size, urbanization and economic growth as relevant determinants into the income inequality model. By applying combined cointegration method of Bayer–Hanck (J Time Ser Anal 34(1): 83–95, 2013) and ARDL bounds testing of cointegration approach of Pesaran et al. (J Appl Econom 16(3):289–326, 2001); it finds that there is the existence of a long-run relationship among the variables in our inequality model for both India and China. After confirming cointegration among the variables, the long-run results based on ARDL model surprisingly revealed that economic globalization widens the income inequality in India but the same factor reduces the income inequality in China. Contrastingly, both the FDI and remittances inflows significantly contribute to reduce income inequality in China, while the same worsens the income inequality in India. In examining the role and effects of structural changes in both the economies from the changing sectoral contributions of output in total output (industry sector and service sectors) in our model, it exposes the fact that the changing sectoral growth contribution has been leading to rising income inequality in China while the same has been resulting in reduction of income inequality in India. The infrastructural development has led to rising income inequality in both the countries, while human capital formation as expected reduces income inequality for both the countries. It also observes that economic growth, urbanization and government size enable both the economies to improve in their pattern of income distribution which have significant implication for public policy of both the economies while aiming at reducing poverty and inequality.
14 schema:genre article
15 schema:inLanguage en
16 schema:isAccessibleForFree false
17 schema:isPartOf N4aac979f400e4b8fbbc9a7fde04571d1
18 N918bb28f4eb54581a85184ff4c6523ac
19 sg:journal.1412840
20 schema:keywords ARDL bounds testing
21 ARDL model
22 Bayer–Hanck
23 China
24 FDI
25 FDI inflows
26 India
27 Pesaran et al
28 al
29 annual data
30 approach
31 bounds testing
32 capital formation
33 changes
34 cointegration
35 cointegration approach
36 cointegration method
37 contribution
38 countries
39 data
40 determinants
41 development
42 distribution
43 economic globalization
44 economic growth
45 economics
46 economy
47 effect
48 et al
49 existence
50 fact
51 factors
52 formation
53 globalization
54 government size
55 growth
56 growth contribution
57 human capital formation
58 implications
59 income distribution
60 income inequality
61 inequality
62 inequality model
63 inflow
64 infrastructural development
65 method
66 model
67 output
68 patterns
69 policy
70 poverty
71 public policy
72 reduction
73 relationship
74 relevant determinants
75 results
76 role
77 role of FDI
78 run relationship
79 run results
80 same factors
81 samples
82 sectoral contributions
83 sectoral output
84 significant implications
85 size
86 structural changes
87 study
88 testing
89 total output
90 urbanization
91 variables
92 schema:name Does globalization exacerbate income inequality in two largest emerging economies? The role of FDI and remittances inflows
93 schema:pagination 443-480
94 schema:productId N01da60c1e29741ae9c0fa036282e485c
95 Nceb5fd2f0b954afbaa494399be9a76f9
96 schema:sameAs https://app.dimensions.ai/details/publication/pub.1127546142
97 https://doi.org/10.1007/s12232-020-00350-0
98 schema:sdDatePublished 2022-05-20T07:36
99 schema:sdLicense https://scigraph.springernature.com/explorer/license/
100 schema:sdPublisher N48217a7120ed4413bc7078c4e8dfb056
101 schema:url https://doi.org/10.1007/s12232-020-00350-0
102 sgo:license sg:explorer/license/
103 sgo:sdDataset articles
104 rdf:type schema:ScholarlyArticle
105 N01da60c1e29741ae9c0fa036282e485c schema:name dimensions_id
106 schema:value pub.1127546142
107 rdf:type schema:PropertyValue
108 N48217a7120ed4413bc7078c4e8dfb056 schema:name Springer Nature - SN SciGraph project
109 rdf:type schema:Organization
110 N4aac979f400e4b8fbbc9a7fde04571d1 schema:issueNumber 4
111 rdf:type schema:PublicationIssue
112 N6b4a510a9c144c2cbaedc5ef2b16c507 rdf:first sg:person.07747377034.81
113 rdf:rest Nd8785da400ff43cb82fa94bdf824be17
114 N918bb28f4eb54581a85184ff4c6523ac schema:volumeNumber 67
115 rdf:type schema:PublicationVolume
116 Nceb5fd2f0b954afbaa494399be9a76f9 schema:name doi
117 schema:value 10.1007/s12232-020-00350-0
118 rdf:type schema:PropertyValue
119 Nd8785da400ff43cb82fa94bdf824be17 rdf:first sg:person.010002330534.20
120 rdf:rest rdf:nil
121 Ndcfce17e10714d4798c2ad3428873658 rdf:first sg:person.015046426225.24
122 rdf:rest N6b4a510a9c144c2cbaedc5ef2b16c507
123 anzsrc-for:14 schema:inDefinedTermSet anzsrc-for:
124 schema:name Economics
125 rdf:type schema:DefinedTerm
126 anzsrc-for:1402 schema:inDefinedTermSet anzsrc-for:
127 schema:name Applied Economics
128 rdf:type schema:DefinedTerm
129 anzsrc-for:1403 schema:inDefinedTermSet anzsrc-for:
130 schema:name Econometrics
131 rdf:type schema:DefinedTerm
132 sg:journal.1412840 schema:issn 1863-4613
133 1865-1704
134 schema:name International Review of Economics
135 schema:publisher Springer Nature
136 rdf:type schema:Periodical
137 sg:person.010002330534.20 schema:affiliation grid-institutes:grid.417969.4
138 schema:familyName Padhan
139 schema:givenName Hemachandra
140 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010002330534.20
141 rdf:type schema:Person
142 sg:person.015046426225.24 schema:affiliation grid-institutes:grid.433028.e
143 schema:familyName Mallick
144 schema:givenName Hrushikesh
145 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015046426225.24
146 rdf:type schema:Person
147 sg:person.07747377034.81 schema:affiliation grid-institutes:grid.429017.9
148 schema:familyName Mahalik
149 schema:givenName Mantu Kumar
150 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07747377034.81
151 rdf:type schema:Person
152 sg:pub.10.1007/bf00138861 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053705392
153 https://doi.org/10.1007/bf00138861
154 rdf:type schema:CreativeWork
155 sg:pub.10.1007/bf02298327 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026589275
156 https://doi.org/10.1007/bf02298327
157 rdf:type schema:CreativeWork
158 sg:pub.10.1007/bf02707386 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001716375
159 https://doi.org/10.1007/bf02707386
160 rdf:type schema:CreativeWork
161 sg:pub.10.1007/s11205-016-1229-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049168704
162 https://doi.org/10.1007/s11205-016-1229-1
163 rdf:type schema:CreativeWork
164 sg:pub.10.1023/a:1009850119329 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018247772
165 https://doi.org/10.1023/a:1009850119329
166 rdf:type schema:CreativeWork
167 sg:pub.10.1057/imfer.2013.7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051945227
168 https://doi.org/10.1057/imfer.2013.7
169 rdf:type schema:CreativeWork
170 grid-institutes:grid.417969.4 schema:alternateName Department of Humanities and Social Sciences, Indian Institute of Technology, Madras, Chennai, Tamil Nadu, India
171 schema:name Department of Humanities and Social Sciences, Indian Institute of Technology, Madras, Chennai, Tamil Nadu, India
172 rdf:type schema:Organization
173 grid-institutes:grid.429017.9 schema:alternateName Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, Medinipur, West Bengal, India
174 schema:name Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, Medinipur, West Bengal, India
175 rdf:type schema:Organization
176 grid-institutes:grid.433028.e schema:alternateName Centre for Development Studies, Trivandrum, Kerala, India
177 schema:name Centre for Development Studies, Trivandrum, Kerala, India
178 rdf:type schema:Organization
 




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


...