本研究欲探討在同期相關之下失業對糧食不安全的影響，資料取自美國普查局、美國勞動統計局、美國經濟分析局、美國農業部及聯邦房屋金融局，本研究主要使用2005年至2015年美國五十州及華盛頓特區失業率、貧窮率及實質人均所得對糧食不安全進行探討分析。糧食不安全分為三個層次，本研究分別為近乎糧食不安全、糧食不安全及低度糧食不安全來進行估計，有別於文獻，本研究探討共同衝擊下，失業率對糧食不安全三層次的影響，採用Pesaran之一般性相關效果混和估計式(CCEP)及一般性相關效果平均估計式(CCEMG)以整體平均的概念來消除這些未觀察到共同因子之同期相關。失業率會對糧食不安全造成極大的影響，然而在去除掉同期相關的情況下，我們發現失業率僅對近乎糧食不安的家戶有影響。
同時本研究也控制人均食品及飲品實質支出、家用食品物價指數、房價指數及營養補充援助計畫作為敏感性分析，本研究以工具變數控制營養補充援助計畫對糧食不安全三層次的內生性。結果顯示：加入敏感性分析變數後，能夠提升失業率對糧食不安全三層次之顯著程度，使失業率不論在任何群集皆為正向且顯著。然而使用CCEP及CCEMG後會把顯著效果消除，因此我們會將重點解釋變數進行排列組合個別對糧食不安全三層次進行研析，並發現CCEP估計式衡量的效果會比CCEMG估計式結果好，而這是因為CCEP估計式較適合我們的樣本大小，控制人均食品及飲品實質支出會比實質人均所得更能顯示出失業率對糧食不安全的影響。

This study is intended to investigate the impact of unemployment on food insecurity in common shocks, and the data are provided by the US Census Bureau, the US Bureau of Labor Statistics, the US Bureau of Economic Analysis, US Department of Agriculture and the Federal Housing and Finance Agency. We mainly use the data of unemployment rate, poverty rate and per capita real GDP from 2005 to 2015 in US states and Washington DC to analyze the impact to food insecurity. Food insecurity in three levels are Marginally food insecurity, Food insecurity and Very low food security, respectively. The contribution of our study is that we analyze the effect of unemployment rate to three levels of food insecurity under common shocks. Then we find that unemployment rate has great impact to food insecurity. After we used common correlated effected estimator to eliminate Cross-Section Dependent, we also find that unemployment rate is only statistically significant for marginally food insecurity households.
After all, we use per capita real food and beverage expenditure by State, food at home consumer price index, house price index and SNAP subsidy rate as controlling variables in the sensitivity analysis. We find that that adding those controlling variables of sensitivity analysis strengthen the impact of unemployment rate to all three levels of food insecurity; that is, the estimates become more significant. After then we estimate the various models by controlling different sets of variables using CCEP and CCEMG estimators. We find that CCEP estimator is more appropriate than CCEMG estimator to fit our model. And adding per capita real food and beverage expenditure is more capable of strengthening the impact of unemployment rate to three levels of food insecurity statistically than per capita real GDP.

目 錄
第一章  緒論	1
  第一節  研究動機	1
  第二節  研究目的	8
第二章  文獻回顧	10
第三章  資料來源與變數定義	13
  第一節  資料來源與處理	13
  第二節  變數定義	16
  第三節  敘述統計	19
第四章  實證模型設定	25
  第一節  靜態縱橫斷面模型	25
  第二節  一般性相關效果估計式(CCE Estimator)	27
  第三節  同期相關檢定(CD test)	31
  第四節  同期相關下之單根檢定	32
第五章  實證結果與分析	34
  第一節  變數之同期相關檢定及同期相關下之單根檢定	34
  第二節  靜態縱橫斷面模型	36
  第三節  一般性相關效果估計式(CCE)	38
  第四節  增長率模型於一般性相關效果估計式(CCE)之解析	40
  第五節  其他解釋變數之敏感性分析	45
第六節  營養補充援助計畫之敏感性分析	54
　第七節  小結	64
第六章  結論	66
  第一節  總結	66
  第二節  研究限制及經濟意涵	68
參考文獻	70
附錄	72 

表目錄
表3-1所使用之美國洲別及大都會區域		14
表3-2變數定義及說明		18
表3-3所使用變數之敘述統計		19
表3-4近乎糧食不安全之變數相關矩陣		24
表3-5糧食不安全之變數相關矩陣		24
表3-6低度糧食安全之變數相關矩陣		24
表5-1變數之單根檢定		34
表5-2變數之同期相關檢定		35
表5-3靜態縱橫斷面模型結果		36
表5-4一般性相關效果估計式		38
表5-5一般性相關效果混和估計式(CCEP estimator)下之排列組合		41
表5-6一般性相關效果平均估計式(CCEMG estimator)下之排列組合		42
表5-7敏感性分析之其他變數單根檢定		46
表5-8敏感性分析之其他變數同期相關檢定		47
表5-9敏感性分析之其他變數靜態縱橫斷面模型結果		48
表5-10敏感性分析之其他變數一般性相關效果估計式結果		51
表5-11敏感性分析之營養補充援助計畫變數單根檢定		54
表5-12敏感性分析之營養補充援助計畫變數同期相關檢定		55
表5-13敏感性分析之營養補充援助計畫變數靜態縱橫斷面模型結果		56
表5-14敏感性分析之SNAP之補助率及其工具變數靜態縱橫斷面模型結果		59
表5-15敏感性分析之SNAP之補助率估計值於靜態縱橫斷面模型結果		60
表5-16敏感性分析之SNAP之補助率前一期估計值於靜態縱橫斷面模型結果		61
表5-17敏感性分析之SNAP之補助率前一期估計值一般性相關效果估計式結果		62
 
圖目錄
圖1-1全美國歷年糧食不安全平均趨勢圖		2
圖1-2失業率對糧食不安全三個層次之歷年全美國平均趨勢圖		7
圖3-1歷年美國五十州及華盛頓特區之近乎糧食不安全洪流圖		20
圖3-2歷年美國五十州及華盛頓特區之糧食不安全洪流圖		21
圖3-3歷年美國五十州及華盛頓特區之低度糧食不安全洪流圖		22
圖3-4歷年美國五十州及華盛頓特區之失業率洪流圖		23

附錄
A.1糧食不安全核心問題之問卷		72
A.2貧窮率對糧食不安全三個層次之歷年全美國平均趨勢圖		74
A.3實質人均所得對糧食不安全三個層次之歷年全美國平均趨勢圖		75
A.4人均食品及飲品實質支出對糧食不安全三個層次之全美國平均趨勢圖		76
A.5家用食品消費者物價指數對糧食不安全三個層次之歷年全美國平均趨勢圖		77
A.6房價指數對糧食不安全三個層次之歷年全美國平均趨勢圖		78

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