失業率是衡量經濟景氣與勞動市場效率的核心指標，其波動會影響社會整體穩定性，透過政策工具預防結構性失業一直是政府的施政重點。本研究以2018年至2024年期間臺灣20個縣市（不包含金門縣、連江縣）追蹤資料為樣本，有效樣本共140個，探討各縣市平均每人就業安定基金是否對失業率造成影響，以及臺灣各縣市之間的失業率是否存在空間相依性及動態效果。本研究使用一般動差法（Generalized Method of Moments，GMM）於動態空間追蹤自我迴歸模型（Dynamic Panel Spatial Auto Regression Model，DPSAR）進行實證估計。
本研究得出以下主要研究結果。首先，實證結果顯示，失業率的空間相關性為正相關，當本地失業率上升，鄰近地區的失業率也會隨之上升，所以應強化區域協作，推動跨縣市治理。再者，動態效果為正向影響，失業率會受到上一期失業率的影響，建議政府建立失業預警機制，在預測到景氣可能轉弱時，提前增加相關預算以應對失業率的時間依賴性。其次，平均每人就業安定基金越多，失業率越低。最後，本研究發現勞動參與率越高，失業率越低；自有住宅率越高，失業率越高；15歲以上民間人口具大專以上教育程度、人均可支配所得、第三級以及第一級產業就業人數則在本研究中效果不顯著。

Unemployment is a key indicator of economic and labor market conditions, and addressing structural unemployment remains a major policy concern. This study analyzes panel data from 20 cities and counties in Taiwan from 2018 to 2024, comprising a total of 140 observations, to investigate the impact of the intensity of Employment Security Fund allocation on local unemployment rates. Additionally, the research explores the potential spatial correlation and dynamic effects of unemployment across these regions. The Generalized Method of Moments (GMM) is employed within a Dynamic Panel Spatial Auto Regression Model (DPSAR) for empirical estimation.
The main findings are as follows: First, the empirical results reveal a positive spatial correlation in unemployment rates, indicating that rising unemployment in one area tends to drive up rates in neighboring regions. Second, a positive dynamic effect is observed, where current unemployment is significantly influenced by past levels, indicating the persistence of unemployment. Regarding the explanatory variables, the study finds that higher Employment Security Fund allocation per capita and greater labor force participation are associated with lower unemployment rates, whereas a higher homeownership rate is associated with higher unemployment. Other variables, including civilian population aged 15 and over with junior college or higher education, disposable income per capita, and employment in the primary and tertiary sectors, are found to be statistically insignificant.

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