都市生產力與聚集經濟之研究: 資料包絡分析之應用

Abstract

區位對於經濟活動與產業生產力力是具有重大的影響力，這也是區位理論語屋市經濟學之所以重要的原因，也因此才會產生不同的都市人口分布與產業類型的地區。故在都市經濟學當中，往往先建立起都市生產函數的型態，來估計出各都市的生產力以及該地區最具有比較利益優勢或專業化生產的產業。本計畫不同於過往許多研究是使用迴歸分析來作估計，而是引用資料包絡分析法來進行研究與分析。其優點在於不需要事先設定出任何型態的生產函數或特殊假設條件。首先在資料包絡分析法之下，利用台灣各度市的整體產業資料，以找出生產效率分數最高的都市。接著，將產業細分為製造業的中分類，計算出各產業在各都市的生產效率分數，我們可以進一步瞭解個別產業的最佳生產力的區位應選擇於何處，這對於產業區位選擇有正面的幫助。當然，都市生產力會產生差異性，很可能與都市規模與階層有所關聯性，也就是聚集經濟中的都市化經濟有關，結果我們可以發現中小型都市，整體來說對於製造業各產業的生產力的好處較大都市來說更為顯著。但這些中小都市仍以大都會區周圍都市最為有利，顯然市場與人力的考量仍然很重要。最後，我國是一個以出口導向為主的國家，因此產業的變遷非常地快速，本計畫也希望藉由不同年度資料作實證結果的比較，以進一步分析我國產業未來生產力與區位選擇的趨勢

Productivity of every city is different due to variation of location. Further urban productivity difference is often used to explain urban growth or decline. Based on this, estimating urban production function is a critical research. Past studies almost focused on regression analysis, but this paper will suggest Data Envelopment Analysis (DEA) to provide many advantages over regression analysis for estimating productivity efficiency of production units. One of these benefits are nonparametric method for production function. We will apply DEA to estimate and order productivity efficiency scores and we can find a city of best performance of urban productivity. In addition, by use of two-digit manufacture industries, this study will can obtain the best location choice for the certain industry. In turn, we want to try to know which factors affect urban productivity. A general and traditional explanation is agglomeration economies and city-size distribution. This project will search correlation between city size and urban productivity. We find that in general, small or medium cities will provide better productivity than some big cities. These cities mostly lie around the big metropolitan area. This makes us better understanding the loacation choice of specific industry. Finally, Taiwan is a small open economy and changes of its industrial structure are very fast. We will use many annual data to estimate and compare alternation of urban productivity. This will make us understand better about time trend of urban and industrial development.