近年來，台灣面臨生育率持續下降與人口老化加劇的雙重挑戰，少子化已成為影響國家經濟發展與社會結構的重要議題。雖然政府已透過增加生育補助與完善托育政策以提升生育意願，然而效果有限，顯示僅從降低育兒成本切入仍不足以解決根本問題。國內外研究逐漸指出，所得分配不均與區域發展差異可能深刻影響家庭的生育決策。因此，本研究旨在探討台灣縣市層級所得分配結構對出生率之影響，並進一步檢驗是否存在空間擴散效應。
本研究以2014年至2023年台灣20縣市面板資料為基礎，運用空間自我迴歸模型（SAR）進行實證分析，同時控制人口密度、服務業比例、老年人口比例、失業率、可支配所得、女性勞動參與率、嬰兒死亡率、經濟發展支出及社會福利支出等變數。研究結果顯示，所得不均對當地出生率具有顯著負向影響，且鄰近地區之出生率亦會透過空間自我相關效應影響本地出生率，驗證了地區間少子化問題存在擴散現象。此外，控制變數如失業率與高人口密度亦顯示對出生率有抑制效果，而經濟發展支出與社會福利支出則對改善生育環境具正面效益。
本研究結果不僅補足國內對「所得分配與少子化」議題在區域與空間層次之研究缺口，更提供政策面重要啟示：未來應將縮減所得差距與提升社會資源再分配，作為促進生育政策的重要配套，並針對高不均地區加強托育與住宅支持，減輕青年家庭的經濟與育兒壓力，以因應台灣日益嚴峻的人口挑戰。

In recent years, Taiwan has faced the dual challenges of a continuously declining birth rate and an increasingly aging population. The issue of low fertility has become a critical concern impacting national economic development and social structure. Although the government has implemented various policies, such as increased childbirth subsidies and improved childcare services, these measures have achieved limited success, indicating that focusing solely on reducing child-rearing costs is insufficient to address the root causes. Domestic and international studies increasingly suggest that income inequality and regional development disparities profoundly influence household fertility decisions. Therefore, this study aims to examine the impact of income distribution at the county level on birth rates in Taiwan and further investigate whether spatial spillover effects exist.
This research utilizes balanced panel data from 20 counties in Taiwan spanning from 2014 to 2023 and employs the Spatial Autoregressive (SAR) model for empirical analysis. Several control variables are included, such as population density, the proportion of employment in the service sector, the proportion of the elderly population, unemployment rate, disposable income, female labor force participation rate, infant mortality rate, economic development expenditure, and social welfare expenditure. The results reveal that income inequality has a significant negative impact on local birth rates and that the birth rates of neighboring regions also affect local fertility through spatial autocorrelation, confirming the existence of a spatial diffusion phenomenon of low fertility. Moreover, control variables such as higher unemployment rates and population density show inhibitory effects on birth rates, while economic development and social welfare expenditures positively contribute to improving the fertility environment.
The findings of this study not only fill the domestic research gap regarding the relationship between income distribution and fertility from a regional and spatial perspective but also provide important policy implications. To address Taiwan’s increasingly severe demographic challenges, future fertility policies should focus on narrowing income disparities and enhancing social resource redistribution, while strengthening childcare and housing support in areas with high inequality, thereby reducing the economic and parenting burdens on young families.

參考文獻
一、中文文獻
王英（2022），「我國人口出生率影響因素研究」，《運籌與模糊學》, 12（2），212–224。
任強、沃夫岡（2023），《人口密度和生育率：一項探索性分析》。北京：中國人口科學。
喬曉春（2024），「中國人口老齡化的過去、現在和未來」，《社會政策研究》，47，47–55。
二、外文文獻
山口一男（2005），《女性の労働力参加と出生率の真の関係について：OECD諸国の分析》。东京都：經濟產業研究所（RIETI Discussion Paper Series 05-J-036）。
朝日幸代（2016），《女性就業者の産業別出生率に関する研究－同居児法による全国と都道府県別推計－》。名古屋：中京大學經濟學部研討論文，Discussion Paper Series April 2016 No. 1602。https://www.chukyo-u.ac.jp/research_2/cuie/img/discussionPdf/1602.pdf
Behrman, Julia and Pilar Gonalons-Pons (2020), “Women’s Employment and Fertility in a Global Perspective (1960–2015).” Demographic Research, 43, 707–744.
Cowan, Sarah K. and Kiara Wyndham Douds (2020), “The Effects of Income on Birth Rates: The Case of a Universal Cash Transfer.” American Sociological Review, 47(1), 789-819.
Currie, Jos and Schwandt Hannes (2014), “Short- and Long-Term Effects of Unemployment on Fertility.” Proceedings of the National Academy of Sciences, 14743-14739
Engelhardt, Henriette, Tomas Kögel, and Alexia Prskawetz (2004), “Fertility and Women's Employment Reconsidered: A Macro-Level Time-Series Analysis for Developed Countries, 1960–2000.” Population Studies, 58(1), 109–120.
Hackman, Joseph and Daniel Hruschka (2020), “Disentangling Wealth Effects on Fertility in 64 Low- and Middle-Income Countries.” Evolutionary Human Sciences, e58, 1–18.
Huang, Jr-Tsung, Jiun¬-Nan Pan, and Tsun-Feng Chiang (2015),“Fertility and crime: Evidence from Spatial Analysis of Taiwan.” Journal of Family and Economic Issues, 43(4) ,197-208.
Kalwij, Adriaan (2010), “The Impact of Family Policy Expenditure on Fertility in Western Europe.” Demography, 47(2), 503–519.
Kearney, Melissa S. and Phillip B. Levine (2014), “Income Inequality and Early Non-Marital Childbearing.” The Journal of Human Resources, 49(1), 1-31.
Li, Jun, Tiantian Li, and Wei Wang (2024), “The Impact of Income Inequality on the Fertility Intention: A Micro Perspective Based on Relative Deprivation.” PLOS ONE, 19(12), e0311991. https://doi.org/10.1371/ journal.pone.0311991.
Leet, Don R. (1977), “Interrelations of Population Density, Urbanization, Literacy, and Fertility”. Explorations in Economic History, 14, 388–401.
Noelke, Clemens, Yu-Han Chen, Theresa L. Osypuk, and Dolores Acevedo-Garci (2019), “Economic Downturns and Inequities in Birth Outcomes: Evidence from 149 Million US Births.” American Journal of Epidemiology, 188(6), 1092–1100. Doi: 10.1093/aje/kwz042.
Oshio, Takashi (2019), “Is a Positive Association between Female Employment and Fertility Still Spurious in Developed Countries?” Demographic Research, 41(45), 1277-1288.
Saha, Unnati Rani and Arthur Van Soest (2018), “Infant Death Clustering in Families: Magnitude, Causes, and the Influence of Better Health Services, Bangladesh 1982–2005.” Population Studies, 65(3), 273–287.
Seltzr, Nathan (2019), “Beyond the Great Recession: Labor Market Polarization and Ongoing Fertility Decline in the United States.” Demography, 56(4), 1463-1493
Wu, Weicong and Xindong Zhao (2024), “Income Inequality and Fertility Behavior: An Empirical Study on China.” Journal of Advanced Computational Intelligence and Intelligent Informatics, 28(4), 816-828.
Yang, Guangli and Liangchen Zhang (2023), “Relationship between Aging Population, Birth Rate and Disposable Income per Capita in the Context of COVID-19.” PLOS ONE, 18(8), e0289781.
https://doi.org/10.1371/journal.pone.0289781
Zhang, Hang, Lanyu Wu, and Yuanhao Li Cheng (2024), “Does Fiscal Expenditure Help to Improve the Fertility Desire of Rural Families? An Empirical Study Based on the CFPS Database.” Finance Research Letters 68, 105964. https://doi.org/10.1016/j.frl.2024.105964.
Zhang, Ting Ting, Xiu-Yun Cai, Xiao-Hui Shi, Wei Zhu, and Shao-Nan Shan (2023), “The Effect of Family Fertility Support Policies on Fertility, Their Contribution, and Policy Pathways to Fertility Improvement in OECD Countries.” International Journal of Environmental Research and Public Health, 20(6), 4790. Doi: 10.3390/ijerph20064790.
三、網站資料與數據來源
中華民國統計資訊網，縣市重要指標，取自網址: https://winstacity.dgbas.gov.tw/DgbasWeb/ZWeb/StateFile_ZWeb.aspx.