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Fertility Rates Around the World: A Cluster Analysis of Time Series Data from 1960 to 2013

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Gender Issues in Business and Economics

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

Abstract

The entry of women into the labor market with an active and permanent presence is, today, a subject of a heated debate among scholars and policy makers that sees, on the one hand, diversity in gender relations and women’s employment and on the other hand the economic importance of women and increasing economic efficiency. At international level, greater economic and political role of women is recognized as a sign of economic vitality of the country. The increase in female education rates, the economic and cultural globalization, public policies favorable to families, and recent legislative impositions have enlivened this debate highlighting two crucial aspects: a greater integration of women meeting the equitable principles of equal opportunities and a greater integration of women responding to greater efficiency and economic growth. The main limitations and difficulties in the participation of women in the labor market are numerous and complex and often interconnected: direct discrimination, occupational segregation, stereotypes, conciliation of life and work, the service coverage rates, etc.

In this paper we use World Bank data on fertility rates around the world from 1960 to 2013, and we analyze the different time series related to fertility rates of different countries in order to detect different clusters. The classification of different countries considered in different clusters is performed by considering an appropriate clustering methodology and the dynamic time warping distance. At this point we interpret the different clusters in order to considering also the different labor markets and policies as a relevant determinant of the dynamic of the fertility rate over time and a relevant statistical reason of the formation of the cluster. The aim of this paper is to provide how and if greater attention to women considerations could lead to a greater understanding of the obstacles that prevent the full participation of women in the economy and in particular in the labor market. This recognition allows the creation of more targeted assistance programs to address these obstacles thus creating an environment for even better response from policy makers. This paper is organized as follows. In the first section, we present a recent review of the main literature on women in the labor market. The second section presents data. The third section presents the methodology used and the fourth all different statistical results. In the fifth section, we discuss all results obtained. Finally, we conclude.

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Author information

Authors and Affiliations

  1. University of Rome “Niccolò’ Cusano”, Via Don Carlo Gnocchi, 3, 00166, Rome, Italy

    Carlo Drago

  2. Faculty of Business and Law, Kore University of Enna, Viale delle Olimpiadi, 94100, Enna, EN, Italy

    Giuseppina Talamo Researcher in Economics

Authors
  1. Carlo Drago
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  2. Giuseppina Talamo Researcher in Economics
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Corresponding author

Correspondence to Giuseppina Talamo Researcher in Economics .

Editor information

Editors and Affiliations

  1. Department of UNISU, Niccolò Cusano University, Rome, Italy

    Paola Paoloni

  2. Department of Law and Economics of Productive Activities, Sapienza University of Rome, Rome, Italy

    Rosa Lombardi

Appendix

Appendix

2.1.1 Nations Considered

  1. 1.

    Afghanistan

  2. 2.

    Albania

  3. 3.

    Algeria

  4. 4.

    Angola

  5. 5.

    Antigua and Barbuda

  6. 6.

    Argentine

  7. 7.

    Armenia

  8. 8.

    Aruba

  9. 9.

    Australia

  10. 10.

    Austria

  11. 11.

    Azerbaijan

  12. 12.

    Bahamas, The

  13. 13.

    Bahrain

  14. 14.

    Bangladesh

  15. 15.

    Barbados

  16. 16.

    Belarus

  17. 17.

    Belgium

  18. 18.

    Belize

  19. 19.

    Benin

  20. 20.

    Bhutan

  21. 21.

    Bolivia

  22. 22.

    Bosnia and Herzegovina

  23. 23.

    Botswana

  24. 24.

    Brazil

  25. 25.

    Brunei Darussalam

  26. 26.

    Bulgaria

  27. 27.

    Burkina Faso

  28. 28.

    Burundi

  29. 29.

    Cabo Verde

  30. 30.

    Cambodia

  31. 31.

    Cameroon

  32. 32.

    Canada

  33. 33.

    Central African Republic

  34. 34.

    Chad

  35. 35.

    Channel Islands

  36. 36.

    Chile

  37. 37.

    Cinchona

  38. 38.

    Colombia

  39. 39.

    Comoros

  40. 40.

    Congo, Dem. Rep.

  41. 41.

    Congo, Rep.

  42. 42.

    Costa Rica

  43. 43.

    Cote d’Ivoire

  44. 44.

    Croatia

  45. 45.

    Cuba

  46. 46.

    Cyprus

  47. 47.

    Czech Republic

  48. 48.

    Denmark

  49. 49.

    Djibouti

  50. 50.

    Dominican Republic

  51. 51.

    Ecuador

  52. 52.

    Egypt, Arab Rep.

  53. 53.

    El Salvador

  54. 54.

    Equatorial Guinea

  55. 55.

    Eritrea

  56. 56.

    Estonia

  57. 57.

    Ethiopia

  58. 58.

    Fiji

  59. 59.

    Finland

  60. 60.

    France

  61. 61.

    French Polynesia

  62. 62.

    Gabon

  63. 63.

    Gambia, The

  64. 64.

    Georgia

  65. 65.

    Germany

  66. 66.

    Ghana

  67. 67.

    Greece

  68. 68.

    Grenada

  69. 69.

    Guam

  70. 70.

    Guatemala

  71. 71.

    Guinea

  72. 72.

    Guinea-Bissau

  73. 73.

    Guyana

  74. 74.

    Haiti

  75. 75.

    Honduras

  76. 76.

    Hong Kong SAR, China

  77. 77.

    Hungary

  78. 78.

    Iceland

  79. 79.

    India

  80. 80.

    Indonesia

  81. 81.

    Iran, Islamic Rep.

  82. 82.

    Iraq

  83. 83.

    Ireland

  84. 84.

    Israel

  85. 85.

    Italy

  86. 86.

    Jamaica

  87. 87.

    Japan

  88. 88.

    Jordan

  89. 89.

    Kazakhstan

  90. 90.

    Kenya

  91. 91.

    Kiribati

  92. 92.

    Korea, Dem. Rep.

  93. 93.

    Korea, Rep.

  94. 94.

    Kuwait

  95. 95.

    Kyrgyz Republic

  96. 96.

    Lao PDR

  97. 97.

    Latvia

  98. 98.

    Lebanon

  99. 99.

    Lesotho

  100. 100.

    Liberia

  101. 101.

    Libya

  102. 102.

    Lithuania

  103. 103.

    Macao SAR, China

  104. 104.

    Macedonia, FYR

  105. 105.

    Madagascar

  106. 106.

    Malawi

  107. 107.

    Malaysia

  108. 108.

    Maldives

  109. 109.

    Mali

  110. 110.

    Malta

  111. 111.

    Mauritania

  112. 112.

    Mauritius

  113. 113.

    Mexico

  114. 114.

    Micronesia, Fed. Sts.

  115. 115.

    Moldova

  116. 116.

    Mongolia

  117. 117.

    Montenegro

  118. 118.

    Morocco

  119. 119.

    Mozambique

  120. 120.

    Myanmar

  121. 121.

    Namibia

  122. 122.

    Nepal

  123. 123.

    Netherlands

  124. 124.

    New Caledonia

  125. 125.

    New Zealand

  126. 126.

    Nicaragua

  127. 127.

    Niger

  128. 128.

    Nigeria

  129. 129.

    Norway

  130. 130.

    Oman

  131. 131.

    Pakistan

  132. 132.

    Panama

  133. 133.

    Papua New Guinea

  134. 134.

    Paraguay

  135. 135.

    Peru

  136. 136.

    Philippines

  137. 137.

    Poland

  138. 138.

    Portugal

  139. 139.

    Puerto Rico

  140. 140.

    Qatar

  141. 141.

    Romania

  142. 142.

    Russian Federation

  143. 143.

    Rwanda

  144. 144.

    Samoa

  145. 145.

    Sao Tome and Principe

  146. 146.

    Saudi Arabia

  147. 147.

    Senegal

  148. 148.

    Sierra Leone

  149. 149.

    Slovak Republic

  150. 150.

    Slovenia

  151. 151.

    Solomon Islands

  152. 152.

    Somalia

  153. 153.

    South Africa

  154. 154.

    South Sudan

  155. 155.

    Spain

  156. 156.

    Sri Lanka

  157. 157.

    St. Lucia

  158. 158.

    St. Vincent and the Grenadines

  159. 159.

    Sudan

  160. 160.

    Suriname

  161. 161.

    Swaziland

  162. 162.

    Sweden

  163. 163.

    Switzerland

  164. 164.

    Syrian Arab Republic

  165. 165.

    Tajikistan

  166. 166.

    Tanzania

  167. 167.

    Thailand

  168. 168.

    Timor-Leste

  169. 169.

    Togo

  170. 170.

    Tonga

  171. 171.

    Trinidad and Tobago

  172. 172.

    Tunisia

  173. 173.

    Turkey

  174. 174.

    Turkmenistan

  175. 175.

    Uganda

  176. 176.

    Ukraine

  177. 177.

    United Arab Emirates

  178. 178.

    United Kingdom

  179. 179.

    United States

  180. 180.

    Uruguay

  181. 181.

    Uzbekistan

  182. 182.

    Vanuatu

  183. 183.

    Venezuela, RB

  184. 184.

    Vietnam

  185. 185.

    Virgin Islands (U.S.)

  186. 186.

    Yemen, Rep.

  187. 187.

    Zambia

  188. 188.

    Zimbabwe

Group 1 European countries, Italy, Germany, Greece; Eastern European countries, Russia, Romania, Bulgaria; Japan.

Group 2 Anglo-Saxon countries, Scandinavia, France, Belgium, Netherlands.

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Drago, C., Talamo, G. (2018). Fertility Rates Around the World: A Cluster Analysis of Time Series Data from 1960 to 2013. In: Paoloni, P., Lombardi, R. (eds) Gender Issues in Business and Economics. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-65193-4_2

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