外文翻譯--中國國內(nèi)的企業(yè)受益于外國直接投資嗎？

1、<p><b>　　中文4187字</b></p><p>　　本科畢業(yè)論文外文翻譯</p><p>　　外文題目： Do Domestic Chinese Firms Benefit from </p><p>　　Foreign Direct

2、 Investment? </p><p>　　出 處： University of California , Berkeley </p><p>　　作 者： Chang-Tai H

3、sieh </p><p><b>　　原 文：</b></p><p><b>　　Summary</b></p><p>　　This paper uses a unique plant-level panel dataset fro

4、m the Chinese manufacturing sector to measure the effects of foreign firms on the productivity of domestic firms. We find that foreign firms are more productive than domestic firms in the same industry. We find little ev

5、idence that foreign firms had any effect, either positive or negative, on the average productivity of domestic Chinese manufacturing plants. However, we also find clear evidence that this average effect masks important h

6、eterog</p><p>　　1. Introduction</p><p>　　In recent decades, direct foreign investment (DFI) has exploded in developing countries. By some accounts, DFI accounts for more than half of all externa

7、l financing in developing countries. In fact, many policy makers believe that attracting DFI is a crucial ingredient for accelerating the country’s economic development. Foreign firms, the argument goes, would introduce

8、new technologies and help upgrade technological capabilities of domestic firms. This could occur through a variety of channels.</p><p>　　Due to these reasons, many countries have introduced a battery of tax

9、incentives, ranging from tax holidays to the provision of utilities and other infrastructure at concessionary rates. And nowhere is this more apparent than in China, where the government has introduced a number of incent

10、ives to attract foreign investment, with remarkable success so far. In fact, China has emerged as the largest recipients of direct foreign investment in the world. Yet, there is remarkably little evidence on th</p>

11、<p>　　This paper will follow the approach taken by Aitken and Harrison applied to a unique panel dataset of Chinese firms. Specifically, there are two questions we seek to answer. First, do joint ventures or wholl

12、y owned foreign subsidiaries in China have higher levels of productivity than domestic firms in similar sectors? Second, does the presence of foreign firms (either joint ventures or wholly owned foreign firms) result in

13、a technology “spillovers” to domestic firms?</p><p>　　We report three main findings. First, foreign firms are indeed more productive than domestic firms in the same sector. Second, the presence of foreign fi

14、rms in a sector does not appear to have an effect, either positive or negative, on the productivity of an average plant in the sector. Third, foreign penetration in a sector has important effects on inequality: large dom

15、estic plants appear to be benefit from the presence of foreign firms, while small domestic plants appear to suffer. This paper </p><p>　　whether the spillovers are local in nature. Section 5 looks for eviden

16、ce that foreign capital had a differential effect for large versus small firms. Section 6 concludes.</p><p><b>　　2. Data</b></p><p>　　The data used in this paper is the firm level da

17、ta from the Chinese Annual Survey of Industries conducted annually by China’s National Bureau of Statistics. This is the data published in the industrial statistics chapter of the annual publication of China’s Statistica

18、l Yearbook. We have this data from 1998 through 2004. This survey covers all state plants and all non-state plants with revenues greater than 5 million Yuan. The number of plants ranges from 200,000 to 250,000. The data

19、also provide</p><p>　　The pieces of information we use from this dataset are the following. First, we define the plant’s industry as a 3-digit level. There are roughly 180 3-digit industries in the data. Sec

20、ond, we use the plant’s revenues, employment, input costs, and the book value of the capital stock to measure the plant’s productivity. The use of the book value of the capital stock instead of the market value may be of

21、 concern. One way in which we tried to deal with this is to use the data on the age of the firm</p><p>　　Third, a key piece of information provided in the data is the ownership of the plant. Specifically, th

22、e dataset provides information on the ownership of the plant divided into state, local governments, cooperative, and foreign ownership. We use this information to construct three variables. First, we construct a variable

23、 measuring the foreign ownership share of the plant. We call this variable Plant_DFI. Second, we construct a variable measuring the share of foreign firms in each 3-digit industr</p><p>　　Specifically, we me

24、asure the foreign share in an industry as a weighted average of the employment share of each plant where the weights are the share of foreign equity in each plant. We call this variable Sector_DFI. Finally, we construct

25、a variable for the importance of foreign firms in a geographic region. Specifically, we define the local region as a Chinese province, and measure the share of foreign firms as a weighted average of the employment share

26、of each plant in the province, where the </p><p>　　3. Do Domestic Firms Benefit from Foreign Firms?</p><p>　　To estimate the effect of foreign firms, we follow Aitken and Harrison (1999) and est

27、imate the following log linear production function:</p><p>　　Here, i indexes the plant, j indexes the sector, and t represents time. As for the variables, Y is gross output of the firm, Plant_DFI represents

28、the share of foreign equity for the plant, Sector_DFI represents the employment share of foreign equity in the sector, and Controls denotes a vector of controls (a vector of time dummies, the cost of intermediate inputs,

29、 the employment of the plant, and the book value of the capital stock).</p><p>　　Table 1 presents the basic results from estimating equation (1.1) on the Chinese data. The dependent variable is the log of pl

30、ant gross output, which is regressed on the measures of foreign participation, the number of workers employed in the firm, the value of intermediate inputs used by the firm, and the book value of the capital stock (the l

31、ast three variables are introduced in logs). In addition, in all the regressions we include a vector of time dummies. In the first column, we also include</p><p>　　In contrast, the coefficient on the foreign

32、 ownership in the sector (Sector_DFI) does not appear to be statistically different from zero. This result suggests that foreign presence in a sector (as opposed to being foreign owned itself) does not appear to have any

33、 effect on the productivity of domestic firms.</p><p>　　The coefficient on the term interacting foreign ownership of the plant and foreign ownership in the sector (Plant_DFI*Sector_DFI) is negative and stati

34、stically significant.</p><p>　　The negative coefficient suggests that for domestic plants, there are positive spillovers from foreign investment, in contrast to foreign plants. Note that this result differs

35、from what Aitken and Harrison (1999) found in their analysis of Venezuelan manufacturing plants.</p><p>　　The second column presents the coefficients from the same regression, but omits the industry dummies.

36、 The reason this is done is so that we can compare our results with studies that use only aggregated industry data. As can be seen, the coefficient on foreign ownership in the sector is now negative and statistically sig

37、nificant. The point estimate indicates that the productivity of domestic plants is 4.5 percentage points lower in an industry with 10 percentage point higher foreign share. The co</p><p>　　The third column i

38、ncludes the industry dummies but omits the factor inputs. The reason we do this is to examine the effect of foreign ownership on the scale of domestic plants. In the third column, the coefficient on the foreign share in

39、the industry is large and negative (and precisely estimated). The point estimate indicates that a 10 percent increase in foreign ownership share lowers the output of domestic firms by 3.5 percent.</p><p>　　T

40、his suggests that foreign ownership forces domestic plants to contract. The last four columns in Table 1 examine the dynamic effect of foreign investment by taking differences of the data. Column 5 takes first difference

41、s, Column 6 takes second differences, Column 7 takes third differences, and Column 8 takes four differences of the data. The coefficient on the share of foreign firms in the sector (Sector_DFI) becames more negative as

42、we move from the first difference specification to the four</p><p>　　4. Are the Effects of Foreign Firms Localized?</p><p>　　We now explore whether foreign capital only has an effect on the prod

43、uctivity of local firms in the local area. So far, we have searched for the effect of foreign firms on the productivity of domestic firms in the same industry regardless of the geographic location of the foreign firm or

44、of the domestic firm. However , the textile sector in Shanghai will have much of an effect on the productivity of a domestic firm in the same textile in a far away province such as Gansu. To examine this, we ent</p>

45、;<p>　　We deal with this omitted variable bias in two ways. First, we control for</p><p>　　regional GDP. These estimates are seen in the second column in Table 2. As can be seen, there seems to be cle

46、ar evidence that foreign presence in a region has a large and positive effect on the productivity of domestic firms.</p><p>　　A second approach we take is to estimate “within” estimates by subtracting each v

47、ariable from its plant specific mean over time. The idea is that this would deal the omitted fixed characteristics of each plant by only using the deviation of the variables from its mean over time. Here, the estimates p

48、rovide little evidence that foreign penetration has a positive effect on the productivity of domestic firms in the province. This does not change even when provincial GDP is included on the right han</p><p>

49、　　5. Do the Effect of Foreign Firms Differ by Plant Size?</p><p>　　We now present estimates separately for large and small plants. Here, we define large plants as those with more than 125 employees. As can b

50、e seen, there is generally little difference in the own-plant effect between large and small plants. For example, the OLS estimate on Plant_DFI is virtually the same for small plants as in large plants. In both cases, th

51、e point estimate suggests that foreign owned plants are generally more productive than domestic plants, by roughly 14 percentage points.</p><p>　　However, the effect of foreign investment in a sector does se

52、em to clearly differ between large and small plants, at least when one considers the OLS estimates. For small plants, foreign presence in the sector appears to be associated with lower productivity.</p><p>　

53、　For large plants, the converse is true. Specifically, for small domestic plants, a 10 percentage point increase in the employment share of foreign firms in the sector is associated with a 1.2 percentage point decline in

54、 productivity. For large domestic plants, a similar increase in the share of foreign firms in the sector is associated with a 1 percentage point increase in productivity. This finding is important in understanding the pr

55、evious finding that foreign presence in a sector does not app</p><p>　　6. Conclusion</p><p>　　In this paper, we have exploited a unique panel dataset of Chinese firms in the manufacturing sector

56、 to get at the perennial question of the effect of foreign direct investment on the productivity of domestic firms. Clearly, this is a topic of major relevance for policy. Many countries have viewed the attraction of for

57、eign capital as central to their development strategy, and China has certainly been a major player in this.</p><p>　　This paper follows the approach taken by Aitken and Harrison (1999) to examine the effect

58、of foreign capital in China. Our findings suggest that foreign firms are indeed more productive than domestic firms. When we examine the average productivity of domestic plants in the same sector, we find little evidence

59、 that foreign presence had a positive effect. However, when we unpack this effect, we find clear evidence that foreign presence in a sector had a large and positive effect on large domestic </p><p><b>

60、　　譯 文：</b></p><p>　　中國國內(nèi)的企業(yè)受益于外國直接投資嗎？</p><p>　　Abstract摘要</p><p>　　本文采用中國制造業(yè)的面板數(shù)據(jù)來to measure the effects of foreign firms on the productivity of domestic firm衡量外國公司對(duì)國內(nèi)企業(yè)生產(chǎn)率

61、的影響。We f我們發(fā)現(xiàn)在同一行業(yè)中外國公司要比國內(nèi)企業(yè)的生產(chǎn)率高很多。但外國公司對(duì)國內(nèi)制造業(yè)的平均生產(chǎn)率沒有任何積極或消極的影響。However, we also find然而，我們找到的明確證據(jù)表明，這個(gè)面板數(shù)據(jù)掩蓋了重要的企業(yè)異質(zhì)性：國內(nèi)大公司大大受益于現(xiàn)存的外國直接投資，而國內(nèi)小公司則沒能從中受益。This paper uses a unique plant-level panel dataset from the Chines

62、e manufacturing sector</p><p>　　一、Introduction引言</p><p>　　In recent decades, direct foreign investment (DFI) has exploded in developing 近幾十年來，外國直接投資（FDI）已經(jīng)在發(fā)展中國家急速增長。事實(shí)上，許多決策者認(rèn)為，吸引外商直接投資是加快國家經(jīng)濟(jì)發(fā)

63、展的一個(gè)關(guān)鍵。論證焦點(diǎn)是，外國公司采用的新技術(shù)將幫助提高國內(nèi)企業(yè)的技術(shù)能力。這是可以通過多種渠道實(shí)現(xiàn)的。例如，外國公司的中國員工可以學(xué)習(xí)該外國公司的新技術(shù)并且將這些技術(shù)傳播到自己創(chuàng)辦的公司或移動(dòng)到其他國內(nèi)公司。它可能在外國公司通過刺激上游和下游之間的聯(lián)系以幫助提升國內(nèi)公司技術(shù)。</p><p>　　由于以上原因，許多國家都推出了更好的稅務(wù)優(yōu)惠，從稅收假日提供公用設(shè)施到其他在利率上的優(yōu)惠，沒有一個(gè)國家做的比中國更好

64、了，那里的政府已經(jīng)提出了許多獎(jiǎng)勵(lì)措施，吸引外國投資，至今已創(chuàng)造出不凡的成績。事實(shí)上，中國已成為世界上外商投資的最大直接受益者。然而，卻沒有證據(jù)表明外國公司對(duì)中國國內(nèi)的企業(yè)有任何消極的影響。最近有一個(gè)重要論文，由艾特肯和哈里森（1990）著，他們使用先進(jìn)的計(jì)量技術(shù)，利用來自于委內(nèi)瑞拉的企業(yè)數(shù)據(jù)來測(cè)算出外國企業(yè)對(duì)國內(nèi)企業(yè)生產(chǎn)率的影響程度。最終，艾特肯和哈里森（1999）發(fā)現(xiàn)，外國直接投資對(duì)國內(nèi)企業(yè)的生產(chǎn)率并沒有影響。</p>

65、<p>　　本文將沿用艾特肯和哈里森的方法，采用獨(dú)特的面板數(shù)據(jù)來研究中國公司。具體來說，有兩個(gè)問題我們要解決。首先，在中國的合資或外國獨(dú)資子公司比國內(nèi)有類似部門的企業(yè)擁有更高的生產(chǎn)率水平嗎？第二，現(xiàn)存的外國企業(yè)（無論是合資或獨(dú)資外國公司）是否將技術(shù)“外溢”到了東道國的企業(yè)？</p><p>　　我們提出三個(gè)結(jié)論。首先，外國公司的確比國內(nèi)同一行業(yè)的企業(yè)更有效率。 </p><p>

66、　　其次，一個(gè)行業(yè)的外國公司對(duì)國內(nèi)公司的平均生產(chǎn)率并沒有產(chǎn)生影響，無論是積極或消極的。第三，一個(gè)行業(yè)的國外滲透占重要的不平衡的影響：國內(nèi)大型企業(yè)似乎是受益于現(xiàn)存的外國公司，而國內(nèi)小企業(yè)似乎并未受益。 </p><p>　　本文提供了大量關(guān)于外國投資對(duì)國內(nèi)企業(yè)生產(chǎn)率產(chǎn)生影響的資料。除了上面提到的文件，其他的還包括Blomstrom（ 1986年）墨西哥制造業(yè)和加拿大的Globerman（ 1979年）。至于中國，我

67、們沒看到有任何文章使用了一級(jí)的公司資料來研究外國投資對(duì)中國國內(nèi)企業(yè)生產(chǎn)率的影響。因此，本文的主要貢獻(xiàn)是首先證明了一個(gè)國家的外國資本帶來的資本，而這些外國資本絕大部分來自于世界范圍內(nèi)的外商投資。</p><p>　　本文的結(jié)構(gòu)如下。第2節(jié)描述的數(shù)據(jù)用于分析。第3節(jié)在審查外國投資與生產(chǎn)率關(guān)系的基礎(chǔ)上，提出實(shí)證結(jié)論。第4節(jié)審查外溢是否是地區(qū)特性。第5節(jié)尋找證據(jù)支持，外國資本對(duì)大企業(yè)和小企業(yè)有不同的影響。第6節(jié)結(jié)論。 &

68、lt;/p><p><b>　　二、數(shù)據(jù)</b></p><p>　　The data used in this paper is the firm level data from the Chinese Annual Survey本文所使用的數(shù)據(jù)是公司第一手的數(shù)據(jù)，是由中國國家統(tǒng)計(jì)局統(tǒng)計(jì)的每年一次的中國工業(yè)調(diào)查。這些數(shù)據(jù)公布在中國統(tǒng)計(jì)年鑒工業(yè)那一章。數(shù)據(jù)是從1998年到

69、2004年。這項(xiàng)調(diào)查覆蓋了所有國有和非國有的收入大于5億元的工廠。這些工廠大概有20萬至25萬個(gè)。該數(shù)據(jù)還提供了工廠標(biāo)識(shí)符，因此我們能夠隨著時(shí)間跟蹤這些工廠。對(duì)于每一個(gè)工廠，還提供了該廠的行業(yè)，地理位置，所有權(quán)，資本存量的賬面價(jià)值，投入成本，收入，就業(yè)與收入。 </p><p>　　還有部分信息我們使用如下數(shù)據(jù)。首先，我們以三位數(shù)水平來確定工廠所在的產(chǎn)業(yè)。數(shù)據(jù)中大約有180個(gè)3位數(shù)產(chǎn)業(yè)。第二，我們使用工廠的收入，

70、就業(yè)，投入成本，和資本存量的賬面價(jià)值來衡量工廠的生產(chǎn)率。使用資本存量的賬面價(jià)值而沒有使用市場(chǎng)價(jià)值可能會(huì)成為一個(gè)關(guān)注的問題。我們?cè)噲D處理的方法就是，用不變?cè)鲩L率的假設(shè)和資本存量的賬面價(jià)值來替代資本的市場(chǎng)價(jià)值。結(jié)論如下，不論我們選擇用資本存量的賬面價(jià)值還是用代理的市場(chǎng)價(jià)值結(jié)果都是正確的。（如有需要我們可以很容易的證明這一點(diǎn)）。第三，數(shù)據(jù)中的關(guān)鍵是工廠的所有權(quán)。具體來說，數(shù)據(jù)提供的信息中所有權(quán)分為國家，地方政府，合作以及外國所有權(quán)。我們利用此

71、信息構(gòu)建三個(gè)變量。首先，我們建造一個(gè)變量衡量工廠的外資持股份額。我們稱這個(gè)變量Plant_DFI 。 第二，我們構(gòu)建一個(gè)變量衡量每一個(gè)3位數(shù)產(chǎn)業(yè)外國公司所占的份額。具體來說，我們衡量外國資本在工業(yè)中的比重時(shí)，常常使用衡量就業(yè)率的加權(quán)平均數(shù)，其中權(quán)重是每個(gè)工廠的外國資本所占的份額。我們將此變量稱為 Sector_DFI。最后，我們構(gòu)建一個(gè)變量來衡量在一個(gè)地理區(qū)域中外國公司的重要性。具體來說，我們以中國的省作為區(qū)域的劃分，我們用</p

72、><p>　　三、國內(nèi)企業(yè)是否受益于外國投資？</p><p>　　To estimate the effect of foreign firms, we follow Aitken and Harrison (1999) and 在評(píng)估外國公司的影響時(shí)，我們運(yùn)用艾特肯和哈里森（ 1999年）的方法，得出了下面的log線性生產(chǎn)函數(shù)： </p><p>　　在這里，

73、i指工廠，j指部門，而t代表時(shí)間。至于那幾個(gè)變量，Y 是公司的生產(chǎn)總值，Plant_DFI代表工廠的外國資本份額。Sector_DFI代表外國資本在該部門的就業(yè)份額，而Controls是指控制的矢量（是虛擬時(shí)間，中間投入成本，工廠的就業(yè)，以及資本存量賬面價(jià)值的載體） 。 </p><p>　　Table 1 presents the basic results from estimating equation (

74、1.1) on the Chinese表1在中國數(shù)據(jù)的基礎(chǔ)上介紹了估計(jì)方程（1.1）的基本的結(jié)果。依賴于變量是工廠生產(chǎn)總值的記錄，是外國參與措施的回歸，該公司The dependent variable is the log of plant gross output, which is regressed on the該公司雇用的工人人數(shù)，被公司所用的中間投入的價(jià)值，of intermediate inputs used by the

75、 firm, and the book value of the capital stock (the last以及資本存量的賬面價(jià)值（最后的three variables are introduced in logs).最后d三個(gè)變量均在記錄中介紹了）。此外，在所有的回歸中我們包括了虛擬時(shí)間矢量時(shí)間。In the first column, we also include a vector of 3-digit industry在第&

76、lt;/p><p>　　In contrast, the coefficient on the foreign ownership in the sector ( Sector_DFI ) </p><p>　　與此相反，部門中外國所有權(quán)系數(shù)（Sector_DFI）似乎跟零沒有差異。似乎This result suggests that foreign 這一結(jié)果表明，有外商存在的部門（而不是

77、外商獨(dú)資本身）似乎對(duì)國內(nèi)企業(yè)的生產(chǎn)率沒有任何影響。</p><p>　　The coefficient on the term interacting foreign ownership of the plant and foreign系數(shù)對(duì)于外國所有權(quán)的工廠和外國所有權(quán)的部門的長期相互作用（ Plant_DFI * Sector_DFI ）是消極的并具有統(tǒng)計(jì)學(xué)意義。負(fù)系數(shù)表明：相比國外公司中國公司獲得了來自外國

78、公司積極的技術(shù)外溢。復(fù)習(xí)Note that this result differs from需要注意的是這個(gè)結(jié)果不同于艾特肯和哈里森（1999）分析委內(nèi)瑞拉制造業(yè)的的jiThe second column presents the coefficients from the same regression, but omits結(jié)果。</p><p>　　第二欄從相同的回歸中列出系數(shù)，但略去了行業(yè)虛擬項(xiàng)。我們The

79、 reason this is done is so that we can compare our results with之所以這樣做可以比較我們只用行業(yè)的匯總數(shù)據(jù)研究出的結(jié)果。As can be seen, the coefficient on foreign可以看出，部門的外國所有權(quán)系數(shù)ownership in the sector is now negative and statistically significant.現(xiàn)在

80、是消極的并具有統(tǒng)計(jì)學(xué)意義。這一估計(jì)表明，國內(nèi)工廠的生產(chǎn)率比擁有外資份額高于10個(gè)百分點(diǎn)的行業(yè)低4.5個(gè)百分點(diǎn)。。</p><p>　　。The coefficient on Plant_DFI is 該系數(shù)在Plant_DFI 上仍是積極的，但規(guī)模較小，而且系數(shù)的互動(dòng) Plant_DFI和 Sector_DFI現(xiàn)在變得微不足道。The third column includes the industry dumm

81、ies but omits the factor input第三欄包括工業(yè)模型，但略去了要素投入。我們之所以這樣做的目的是考查外國所有權(quán)對(duì)國內(nèi)工廠規(guī)模的影響。在第三欄，行業(yè)中外國份額的系數(shù)是巨大的和消極的（并且是精確估計(jì)的）。這一估計(jì)表明，外資持股比例百分之十的增長使得國內(nèi)企業(yè)輸出降低了百分之三點(diǎn)五。這表明，外國所有權(quán)推進(jìn)了國內(nèi)企業(yè)的合資。</p><p>　　The last four columns in T

82、able 1 examine the dynamic effect of foreign在表1中的最后四列考查了采取不同數(shù)據(jù)的外國投資的動(dòng)態(tài)影響。第5欄采取第一次的不同，第6欄考慮第二次不同，第7列采取第三次的不同，第8欄采取了四次不同。一個(gè)部門外資份額的系數(shù)（ Sector_DFI ）變得更加負(fù)面，在從第一次的差別到第四次的差別中。這表明國外所有權(quán)對(duì)國內(nèi)生產(chǎn)率的負(fù)面影響隨著時(shí)間的推移變得更加明顯。to the fourth diffe

83、rence specification.這種Thecoefficient on Plant_DFI remains small and statistically insignificant, as is the coefficient系數(shù) Plant_DFI仍然很小并具有統(tǒng)計(jì)學(xué)意義，像on the variable interacting Plant_DFI and Sector_DFI .Plant_DFI和Sector_DFI 的

84、相互作用一樣。 </p><p>　　四、外資影響是否具有地區(qū)特性？</p><p>　　We now explore whether foreign capital only has an effect on the productivity of 我們前面探討是是否在一個(gè)區(qū)域內(nèi)外資只對(duì)當(dāng)?shù)仄髽I(yè)的生產(chǎn)率產(chǎn)生影響。So far, we have searched for the ef

85、fect of foreign firms on 到目前為止，我們已搜查了同一行業(yè)外國公司對(duì)國內(nèi)公司生產(chǎn)率的影響，而不論外國公司或中國公司的地理位置。location of the foreign firm or of the domestic firm.However, given the vastness of然而，鑒于中國土地廣袤，這似乎不大可能說的通，在上海的紡織部門要比國內(nèi)其它偏遠(yuǎn)地區(qū)（如甘肅）企業(yè)的生產(chǎn)率高很多。To exa

86、mine this, we enter a variable for the share of foreign firms in a region </p><p>　　為了審查這點(diǎn)，我們?cè)诜匠蹋?）中給外國企業(yè)的份額增加了一個(gè)變量來表示地區(qū)（以中國省為界定）。這就是，我們定義一個(gè)變量Local_Sector_DFI來表示在一個(gè)限定好的中國省內(nèi)外國公司的就業(yè)份額。很自然的，解釋關(guān)于這個(gè)系數(shù)反映了變量的影響當(dāng)?shù)赝庖?/p>

87、的外國公司是外國公司可以選擇中找到各省特點(diǎn)，也導(dǎo)致更高的國內(nèi)生產(chǎn)率。也就是說，有可能是省略變量，如當(dāng)?shù)鼗A(chǔ)設(shè)施的質(zhì)量影響了外國公司對(duì)地方的決定，在同一省同一生產(chǎn)率水平下。</p><p>　　我們處理這個(gè)遺漏變量偏差的方法有兩種。首先，我們控制區(qū)域國內(nèi)生產(chǎn)總值。這些估計(jì)數(shù)是出現(xiàn)在表2第二列。可以看到，似乎有明確的證據(jù)表明，一個(gè)地區(qū)中外資的存在對(duì)國內(nèi)企業(yè)的生產(chǎn)率有大而積極的影響。</p><p&

88、gt;　　第二種辦法，是去估計(jì)“內(nèi)”估計(jì)值隨著時(shí)間的推移減去工廠中每個(gè)變量。 The idea is that this would deal the此辦法可以省略每個(gè)工廠固有的特性而只考慮隨時(shí)間變化的變量的偏差。這里，估計(jì)值表明外國滲透對(duì)這個(gè)省的企業(yè)生產(chǎn)率并沒有影響。甚至當(dāng)右邊的回歸包括了省的GDP也沒能改變這個(gè)結(jié)果。這里， </p><p>　　五、外資的影響程度是否受工廠規(guī)模大小影響？</p>

89、<p>　　We now present estimates separately for large and small plants.我們現(xiàn)在將估計(jì)值分為大型工廠的和小型工廠的。在這里，我們定義large plants as those with more than 125 employees.有超過125位員工的工廠為大型工廠。可以看出，人們很難分辨大型工廠和小型工廠的區(qū)別的。例如，對(duì) Plant_DFI的OLS估計(jì)不

90、管是大工廠還是小工廠結(jié)果幾乎是一樣的。在這兩種情況下I在zhe，點(diǎn)估計(jì)都表明，外商獨(dú)資工廠要比國內(nèi)企業(yè)的生產(chǎn)率高出約14個(gè)百分點(diǎn)。 </p><p>　　However, the effect of foreign investment in a sector does seem to clearly differ然而，外國投資的部門在用OLS估計(jì)時(shí)，答案則很不同。對(duì)于小型工廠，，外國存在的部門似乎生產(chǎn)率很低。而

91、對(duì)于大型工廠，事實(shí)則是相反。Specifically, for small domestic plants, a 10具體來說，國內(nèi)的小廠，外資部門每10個(gè)百分點(diǎn)就業(yè)份額的增加就會(huì)導(dǎo)致部門生產(chǎn)率下降下降1.2個(gè)百分點(diǎn)。而國內(nèi)大型工廠，有類似的增加則導(dǎo)致該部門的生產(chǎn)率提高了一個(gè)百分點(diǎn)。This finding is important in understanding the這一發(fā)現(xiàn)對(duì)理解前人的發(fā)現(xiàn)是很重要的，也就是理解“外國存在的部門對(duì)

92、國內(nèi)企業(yè)的生產(chǎn)率沒有影響”。前人只注重了以前累計(jì)效應(yīng)，而忽略了重要的異質(zhì)性影響因素，也就是外國資本在大型工廠和小型工廠之間的差別。large and small plants.6</p><p><b>　　六、結(jié)論</b></p><p>　　In this paper, we have exploited a unique panel dataset of Chi

93、nese firms in the 在本文中，我們利用了獨(dú)特的中國制造業(yè)公司的面板數(shù)據(jù)manufacturing sector to get at the perennial question of the effect of foreign direct獲得了對(duì)外國直接投資影響中國國內(nèi)企業(yè)生產(chǎn)率問題的解答。顯然，這是一個(gè)與政策有大相關(guān)的議題。 relevance for policy.Many countries have vi

94、ewed the attraction of foreign capital as許多國家已經(jīng)把吸引外資作為核心central to their development strategy, and China has certainly been a major player in this.核心的發(fā)展戰(zhàn)略，而中國無疑已成為一個(gè)重要的角色。 </p><p>　　This paper follows the ap

95、proach taken by Aitken and Harrison (1999) to examine 本文采取的是與艾特肯和哈里森（ 1999年）相同的辦法，審查了中國利用外資對(duì)中國的影響。中國Our findings suggest that foreign firms are indeed我們的研究結(jié)果表明，外國公司確實(shí)比國內(nèi)企業(yè)更具生產(chǎn)率。當(dāng)我們審查國內(nèi)相同行業(yè)的平均生產(chǎn)率時(shí)，發(fā)現(xiàn)外國投資并沒有對(duì)國內(nèi)企業(yè)生產(chǎn)率產(chǎn)生積極