為因應全球化，各國政府致力於提升政府公共管理績效與效率，評估地方政府績效、資源是否有效運用，政策是否能有效達成治理績效目標及預期結果，縣市政府能否成為全國各機關之標竿典範，著實為重要且複雜議題。為解決地方政府決策單位多元之投入項與產出項，本研究整合各項衡量指標發展一個創新兩階段之治理績效評估程序，運用資料包絡分析法建構臺灣地方政府多年期生產流程之績效評估模型，解決傳統一階段資料包絡分析法模型存在黑箱問題，透過兩階段評估與驗正，精準評估縣市政府績效，據以找出相對效率之標竿縣市政府供其他政府效法與遵循。
本研究首先採用新植基網絡資料包絡分析法，克服傳統資料包絡分析法存在問題，即以非等比例方式測量投入項與產出項之間關係，結合射線與非射線特性測度決策單位相對效率，更能貼近實務情況，提高分析效率準確度。研究目的為先評估地方政府第一階段「稅收效率」，接著評估第二階段「財政效能」，進而運用向量自我迴歸模型，將所有經濟變數均視為應變數，以脈衝響應函數分析政府財產稅政策對「稅收效率」與「財政效能」影響。結果發現：1.政府公告土地現值政策影響「稅收效率」，呈現負向顯著結果。2.政府公告土地地價政策影響「財政效能」，呈現負向顯著結果。其次，本研究運用結合乘法效率整合型之兩階段網絡資料包絡分析法及二階錐規劃函數之測度方法，衡量地方政府「經濟效率」及「財政效能」，進而檢視財產稅稅基之租稅政策對「財政效能」影響，亦建構個別縣市政府管理決策矩陣，分析個別縣市政府治理績效差異。結果發現：1.直轄市政府「經濟效率」及「財政效能」相對非直轄市政府有效率，主要歸因於直轄市政府整合資源充分發揮治理綜效。2.房地稅基之租稅政策對直轄市政府「經濟效率」及「財政效能」相對非直轄市政府有效率。3.個別縣市政府「經濟效率」及「財政效能」多數顯為不同步，部分直轄市政府如桃園市、臺中市及臺南市之「財政效能」呈現無效率，主因係欠稅金額偏高，應強化公務員稅法專業訓練，降低納稅人避稅動機方為上策。
現今全球化政府績效趨於競爭態樣，地方政府稅基之租稅政策影響施政績效，本研究建議地方政府應本於職責範圍，合理調整公告土地現值與公告土地地價，研議差別稅率，俾覈實核定土地稅稅收，或強化地方政府自主財源能力增加稅課收入；現行相關法令規範如有不合時宜，應儘速更新與修訂，據以評估施政結果，作為未來研議政策參考。本研究實證方法可應用於其他公部門或民間組織，檢查資源利用情形，實證結果之研究經驗與方法可作為提升現有資源效率與實現效益最大化參考模式，以實現優質與高效率之政府服務，促進公眾福祉，最終達到滿足公眾對政府期望。

In response to globalization trends, governments worldwide have endeavored to raise their public management performance and efficiency. Local government performance, resource use effectiveness, whether policies help attain governance goals and expected results, and whether a county or city government can provide useful models for other institutions are topics that are crucial and complex. To process the diverse input and output from the decision-making units of local governments, measurement indices were integrated in the present study to develop an innovative two-phase governance performance evaluation model. Data envelopment analysis (DEA) was conducted to construct a model for evaluating the multiyear production performance of local governments in Taiwan to solve black box problems in the conventional single-phase DEA model. Through the two-phase evaluation and verification, the performance of county and city governments was accurately evaluated to identify exemplar local governments with relative efficiency which other local governments can emulate.
A new epsilon-based measure was applied to eliminate problems in the conventional DEA method. A nonproportional method was implemented to investigate the relationship between the input and the output. Radial and nonradial characteristics were combined to measure the relative efficiency of a decision-making unit for improved closeness to actual practices and analysis accuracy. In the first phase, the tax efficiency of a local government was assessed; in the second, its financial efficacy was evaluated. A vector autoregressive model was then applied; with all the economic variables considered as dependent variables, the impulse response function was employed to analyze the effects of the government’s property tax policies on its tax efficiency and financial efficacy. The results indicated that a government’s policies of announced land current value significantly negatively affected both its tax efficiency and financial efficacy. Next, a second-order cone programming function was integrated with the two-phase network DEA model to measure the local government’s economic efficiency and financial efficacy and examine the effect of its property tax base policies on its financial efficacy. An individual county or city government management decision-making matrix was formulated to compare county and city governments’ governance performance. The results revealed that (1) the municipal governments outperformed the nonmunicipal governments in economic efficiency and financial efficacy; this was because the municipal governments have integrated resources to achieve synergy in governance. (2) The property tax base policies of the municipal governments were more effective than those of nonmunicipal governments regarding their economic efficiency and financial efficacy. (3) Most county and city governments exhibited an inconsistency between economic efficiency and financial efficacy; some municipal governments, such as Taoyuan City, Taichung City, and Tainan City, displayed no financial efficacy because of the amount of taxes they owe. The professional training of public servants in tax law must be strengthened, and motivations for taxpayers to evade taxation must be reduced.
The empirical method employed in this study can be applied in other public sectors or private organizations to examine the status of resource use. The empirical research experience and methods provide a reference for improving current efficiency of resource allocation and maximizing efficacy, thereby achieving high-quality and highly efficient government services that enhance public welfare and satisfy people’s expectations of governments. We suggest that local governments, within their jurisdiction, reasonably adjust announced land current values and prices, deliberate on differential tax rates, and thoroughly verify land tax revenues. The central government can strengthen local governments’ independent financial resources, and increase their tax revenues. Outdated laws and regulations should be updated and revised as soon as possible for effective execution. For administrative personnel to carry out policies, enabling the evaluation of governance performance and providing a reference for future policy-making.

一、中文文獻
1.王肇蘭、許義忠、徐偉初(2008)。台灣地區地方政府效率暨生產力之評估。應用經濟論叢，(84)，71-120。
2.王肇蘭、許義忠、賴如庭(2014)。臺灣地區地方稅捐稽徵機關稽徵效率暨生產力之分析。會計審計論叢，4(1)，99-136。
3.李豔玲(1997)。稅捐稽徵機關績效評估之研究。高雄市：國立中山大學公共事務管理研究所碩士學位論文。
4.吳仂(2013)。地方政府支出效率之研究。臺北市：臺灣大學經濟學研究所碩士學位論文，1-62。
5.吳亭瑩(2006)。影響地方財產稅收因素之探討。臺北市：國立政治大學財政研究所碩士學位論文，1-80。
6.吳濟華、劉春初、馮永猷(2010)。台灣地方政府公共支出效率衡量之實證研究。行政暨政策學報，(50)， 33-80。
7.林恭正、陳信嘉(2008)。地方政府資本支出對財產稅收入影響之實證分析。財稅研究，40(2)，66-82。
8.邱荃瑩(2005)。我國地方稅捐稽徵機關績效評估之研究-以資料包絡分析法。桃園市：元智大學會計學系碩士學位論文，1-86。
9.胡議文(2010)。我國地方稅捐稽徵機關稽徵績效之研究－三階段資料包絡分析法之應用。臺北市：國立政治大學碩士論文。
10.陳醇(2015)。縣市改制前後之地方政府績效評估。新北市：臺北大學財政學系碩士學位論文，1-155。
11.陳曉瑩(2002)。台灣地區以土地稅作為地方主要財源之研究。臺南市：成功大學都市計劃學系碩士學位論文，1-102。
12.張瑞真(2003)。從公共選擇觀點探討土地稅稅基之評定。臺北市：國立政治大學地政研究所博士學位論文，1-94。
二、英文文獻
1.Afonso, A., & Fernandes, S. (2008). Assessing and explaining the relative efficiency of local government. The Journal of Socio-Economics, 37(5), 1946-1979.
2.Bagozzi, R. P., & Phillips, L. W. (1982). Representing and testing organizational theories: A holistic construal. Administrative science quarterly, 27(3), 459-489.
3.Balaguer-Coll, M. T., Prior, D., & Tortosa-Ausina, E. (2007). On the determinants of local government performance: A two-stage nonparametric approach. European Economic Review, 51(2), 425-451.
4.Balaguer-Coll, M. T., Prior, D., & Vela-Bargues, J. M. (2002). Efficiency and Quality in Local Government Management: The case of Spanish local authorities (Barcelona: Universitat Autonoma de Barcelona).
5.Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078-1092.
6.Boyd, S., & Vandenberghe, L. (2004). Convex optimization. Cambridge university press.
7.Cao, X., & Yang, F. (2011). Measuring the performance of Internet companies using a two-stage data envelopment analysis model. Enterprise Information Systems, 5(2), 207-217.
8.Charnes, A., & Cooper, W. W. (1962). Programming with linear fractional functionals. Naval Research Logistics Quarterly, 9, 181-185.
9.Charnes, A., Cooper, W. W., & Li, S. (1989). Using data envelopment analysis to evaluate efficiency in the economic performance of Chinese cities. Socio-Economic Planning Sciences, 23(6), 325-344.
10.Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
11.Chen, K., & Zhu, J. (2017). Second order cone programming approach to two-stage network data envelopment analysis. European Journal of Operational Research, 262(1), 231-238.
12.Chen, Y., Cook, W.D., Li, N., & Zhu, J. (2009). Additive efficiency decomposition in two-stage DEA. European Journal of Operational Research, 196(3), 1170-1176.
13.Chiumia, A., & Simwaka, K. (2012). Tax policy developments, donor inflows and economic growth in Malawi. Journal of Economics and International Finance, 4(4), 159-172.
14.Chu, J., Wu, J., Zhu, Q., An, Q., & Xiong, B. (2019). Analysis of China’s regional eco-efficiency: A DEA two-stage network approach with equitable efficiency decomposition. Computational economics, 54(4), 1263-1285.
15.Cook, W. D., Liang, L., Zhu, J. (2010). Measuring performance of two-stage network structures by DEA: a review and future perspective. Omega, 38(6), 423-430.
16.Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1-4.
17.Da Cruz, N. F., & Marques, R. C. (2014). Revisiting the determinants of local government performance. Omega, 44, 91-103.
18.De Borger, B., Kerstens, K., Moesen, W., & Vanneste, J. (1994). Explaining differences in productive efficiency：An application to Belgian municipalities. Public Choice, 80(3-4), 339-358.
19.Du, J., Liang, L., Chen, Y., Cook, W. D., & Zhu, J. (2011). A bargaining game model for measuring performance of two-stage network structures. European Journal of Operational Research, 210(2), 390-397.
20.Eeckaut, P., Tulkens, H., & Jamar, M. A. (1993). Cost efficiency in Belgian municipalities. The Measurement of Productive Efficiency–Techniques and Applications, 300-334.
21.Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35-49.
22.Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
23.Fogarty, J., & Mugera, A. (2013). Local government efficiency: evidence from Western Australia. Australian Economic Review, 46(3), 300-311.
24.Ghobadian, A., & Ashworth, J. (1994). Performance Measurement in Local Government-Concept and Practice. International Journal of Operations & Production Management, 14(5), 35-51.
25.Golany, B., & Roll, Y. (1989). An application procedure for DEA. Omega, 17(3), 237-250.
26.Guo, C., Shureshjani, R. A., Foroughi, A. A., & Zhu, J. (2017). Decomposition weights and overall efficiency in two-stage additive network DEA. European Journal of Operational Research, 257(3), 896-906.
27.Guo, Y., Fu, Y., Chui, E. W. T., & Xue, M. (2017). Equity, efficiency and effectiveness: an evaluation study of the urban minimum livelihood guarantee scheme in China. Journal of Asian Public Policy, 10(2), 143-157.
28.Hu, X., & Liu, C. (2016). Profitability performance assessment in the Australian construction industry: a global relational two-stage DEA method. Construction Management and Economics, 34(3), 147-159.
29.Hu, X., & Liu, C. (2018). Measuring efficiency, effectiveness and overall performance in the Chinese construction industry. Engineering, Construction and Architectural Management, 25(6), 780-797.
30.Huang, S. H., Yu, M. M., Hwang, M. S., Wei, Y. S., & Chen, M. H. (2017). Efficiency of Tax Collection and Tax Management in Taiwan's Local Tax Offices. Pacific Economic Review, 22(4), 620-648.
31.Hunter, W. J., & Nelson, M. A. (1996). An IRS production function. National Tax Journal, 49(1), 105-115.
32.Javaid, M. F. (2017). Expenditure efficiency and fiscal size: An empirical evidence from developing Asian countries. Pakistan Economic and Social Review, 55(1), 247-269.
33.Johnston, J. M., Marlowe, J., Matkin, D. S., & Hayes, M. (2011). The impact of local school property tax reductions on city and county revenue decisions: A natural experiment in Kansas. Public Finance and Management, 11(2), 180.
34.Kao, C. (2009). Efficiency decomposition in network data envelopment analysis: A relational model. European journal of operational research, 192(3), 949-962.
35.Kao, C., & Hwang, S. N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European journal of operational research, 185(1), 418-429.
36.Kao, C., & Hwang, S. N. (2011). Decomposition of technical and scale efficiencies in two-stage production systems. European Journal of Operational Research, 211(3), 515-519.
37.Kao, C., & Hwang, S. N. (2014). Multi-period efficiency and Malmquist productivity index in two-stage production systems. European Journal of Operational Research, 232(3), 512-521.
38.Kapelko, M., Lansink, A. O., & Stefanou, S. E. (2015). Analyzing the impact of investment spikes on dynamic productivity growth. Omega, 54, 116-124.
39.Karkazis, J., & Thanassoulis, E. (1998). Assessing the effectiveness of regional development policies in Northern Greece using data envelopment analysis. Socio-Economic Planning Sciences, 32(2), 123-137.
40.Kistik, V., & Koçak, H. (2016). Data Envelopment Analysis on Performance Measurement of Municipals. European Journal of Business and Management, 8(23), 24-34.
41.Kloot, L., & Martin, J. (2000). Strategic performance management: A balanced approach to performance management issues in local government. Management accounting research, 11(2), 231-251.
42.Liang, L., Cook, W. D., & Zhu, J. (2008). DEA models for two‐stage processes: Game approach and efficiency decomposition. Naval Research Logistics, 55(7), 643-653.
43.Liu, J. S., Lu, L. Y., & Lu, W. M. (2016). Research fronts in data envelopment analysis. Omega, 58, 33-45.
44.Liu, J. S., Lu, L. Y., Lu, W. M., & Lin, B. J. (2013a). Data envelopment analysis 1978–2010: A citation-based literature survey. Omega, 41(1), 3-15.
45.Liu, J. S., Lu, L. Y., Lu, W. M., & Lin, B. J. (2013b). A survey of DEA applications. Omega, 41(5), 893-902.
46.Lobo, M. S., Vandenberghe, L., Boyd, S., & Lebret, H. (1998). Applications of second-order cone programming. Linear Algebra and its Applications, 284(1–3), 193-228.
47.Loikkanen, H. A., & Susiluoto, I. (2005). Cost Efficiency of Finnish Municipalities in Basic Service Provision 1994-2002. Urban Public Economics Review, (4), 39-63.
48.Lu, W. M., & Hung, S. W. (2011). Exploring the operating efficiency of Technology Development Programs by an intellectual capital perspective—A case study of Taiwan. Technovation, 31(8), 374-383.
49.Lu, W. M., Wang, W. K., Hung, S. W., & Lu, E. T. (2012). The effects of corporate governance on airline performance: Production and marketing efficiency perspectives. Transportation Research Part E: Logistics and Transportation Review, 48(2), 529-544.
50.Makrydemetres, A., Zervopoulos, P. D., & Pravita, M. E. (2016). Reform of public administration in Greece; evaluating structural reform of central government departments in Greece: application of the DEA methodology (No. 97). Hellenic Observatory, LSE.
51.Malanga, F. (1986). The relationship between IRS enforcement and tax yield. National Tax Journal, 39(3), 333-337.
52.Marto, B. I., Hakim, A., Wijaya, A. F., & Pratiwi, R. N. (2015). The Performance of Revenue Office in the Perspective of New Public Management-(Study on Performance of Local Tax Management in Makassar, Indonesia). International Journal of Applied, 5(1), 57-62.
53.Mavi, R. K., Saen, R. F., & Goh, M. (2019). Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach. Technological Forecasting and Social Change, 144, 553-562.
54.Mohammad, N., & Noordin, N. (2016). Data envelopment analysis model for measuring efficiency of zakat collection and distribution. e-Academia Journal, 5(2), 210-218.
55.Morais, P., & Camanho, A. S. (2011). Evaluation of performance of European cities with the aim to promote quality of life improvements. Omega, 39(4), 398-409.
56.Nold Hughes, P. A., & Edwards, M. E. (2000). Leviathan vs. Lilliputian： a data envelopment analysis of government efficiency. Journal of Regional Science, 40(4), 649-669.
57.Palmer, A. J. (1993). Performance measurement in local government. Public Money & Management, 13(4), 31–36.
58.Perpiña, I. N., Coll, M. T. B., Petrović, M., & Ausina, E. T. (2017). Which estimator to measure local governments’ cost efficiency? Evidence from Spanish municipalities. In XXIV Encuentro de Economía Pública (p. 24). Universidad de Castilla-La Mancha.
59.Savić, G., Dragojlović, A., Vujošević, M., Arsić, M., & Martić, M. (2015). Impact of the efficiency of the tax administration on tax evasion. Economic research-Ekonomska istraživanja, 28(1), 1138-1148.
60.Sexton, T. R., & Lewis, H. F. (2003). Two-stage DEA: An application to major league baseball. Journal of Productivity Analysis, 19(2-3), 227-249.
61.Shao, L., Yu, X., & Feng, C. (2019). Evaluating the eco-efficiency of China's industrial sectors: A two-stage network data envelopment analysis. Journal of environmental management, 247, 551-560.
62.Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48.
63.Siyuan, L., Chonghuai, N., & Xilong, Y. (2017). Study on Efficiency of Government Fiscal Policy in Process of Enterprise Innovation‒Based on A Perspective of Two-stage Innovation. Science and Technology Management Research, 2017(14), 6.
64.Stine, W. F. (2003). The effect of personal property tax repeal on Pennsylvania's real estate tax growth and stability. National Tax Journal, 56(1), 45-60.
65.Tavana, M., Mirzagoltabar, H., Mirhedayatian, S. M., Saen, R. F., & Azadi, M. (2013). A new network epsilon-based DEA model for supply chain performance evaluation. Computers & Industrial Engineering, 66(2), 501-513.
66.Thirtle, C., Shankar, B., Chitkara, P., Chatterjee, S., & Mohanty, M. S. (2000). Size does matter: technical and scale efficiency in Indian state tax jurisdictions. Review of Development Economics, 4(3), 340–352.
67.Tone, K., & Tsutsui, M. (2009). Network DEA：a slacks-based measure approach. European Journal of Operational Research, 197(1), 243-252.
68.Tone, K., & Tsutsui, M. (2010). An epsilon-based measure of efficiency in DEA–A third pole of technical efficiency. European Journal of Operational Research, 207(3), 1554-1563.
69.Walsh, K. (2012). Understanding taxpayer behaviour–new opportunities for tax administration. The Economic and Social Review, 43(3, Autumn), 451-475.
70.Wang, Q., Hang, Y., Sun, L., & Zhao, Z. (2016). Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach. Technological Forecasting and Social Change, 112, 254-261.
71.Wanke, P. F. (2013). Physical infrastructure and shipment consolidation efficiency drivers in Brazilian ports: A two-stage network-DEA approach. Transport Policy, 29, 145-153.
72.Wanke, P., & Barros, C. (2014). Two-stage DEA: An application to major Brazilian banks. Expert systems with applications, 41(5), 2337-2344.
73.Worthington, A. C. (2000). Cost efficiency in Australian local government：a comparative analysis of mathematical programming and econometrical approaches. Financial Accountability & Management, 16(3), 201-223.
74.Worthington, A., & Dollery, B. (2000). An empirical survey of frontier efficiency measurement techniques in local government. Local Government Studies, 26(2), 23-52.
75.Yadava, A. K., & Neog, Y. (2019). Public Sector Performance and Efficiency Assessment of Indian States. Global Business Review, 1-19.
76.Yin, P., Chu, J., Wu, J., Ding, J., Yang, M., & Wang, Y. (2020). A DEA-based two-stage network approach for hotel performance analysis: An internal cooperation perspective. Omega, 93, 102035.