1、 外文翻译 原文 FDI Determinants: Case of Romania Material Source: springerlink Author:Maria Birsan AE Anuta BuigaAbstract Even if the FDI is important for all host countries, for those in the process of transition to a market economy the FDI presence is critical under many respects. Not all transition cou
2、ntries benefited from the very beginning from the FDI presence. Several determinant factors explain the differences. Romania was lagging behind regarding the interest of foreign investors during the first 910 years of transition. The situation has improved greatly. The aim of this paper is to identi
3、fy the main factors determining the evolution in the FDI/GDP (%) as proxy for the FDI evolution. To this end, we used the method of factors analyses. The four resulted determinant factors are: Market size and potential, Reform progress, Business liberalization, and Labor cost. A linear regression mo
4、del expresses the connections between dependent variable and the four determinant factors. The paper concludes with certain policy implications Keywords: FDI in Romania Reasons for FDI Factor analyses Regression analyses Main determinants JEL Classification F21 F23 Introduction The role of FDI has b
5、een examined under various aspects that refer to the impact on home or host countries, the advantages and the costs. We would mention a few more issues resulting from research, such as the correlation between FDI and the economic growth (cause or effect), the impact of FDI on modernization of econom
6、ic structure and exports, on employment, technology and management transfer, the impact on regional/local development, on payment balance, the tradeoff between FDI and external trade, the impact on exchange rate, etc. Successive evaluations were made about the determinants of FDI, and firms decision
7、s to invest in a foreign country, i.e. about the factors of attractiveness. Besides the above-mentioned issues, when talking about the CEECs as host economies, FDI has played an important role in the privatization of the state sector and, consequently, in promoting the market economy and has also co
8、ntributed significantly to the increased level of competition in this emerging markets. Why do foreign investors choose to invest in the new emerging markets? What are the main determinants that explain the FDI flows towards a country or a group of countries, and what are the motives for the firms d
9、ecisions to take the risk of investing in a certain country? The literature usually categorizes foreign investors according to their reasons for investment as follows: Market seekers: the investors look for new markets. Usually, this kind of FDI is mainly domestic market oriented, and produces what
10、is named horizontal integration (Markusen 1984, developed the most quoted explicative model); Efficiency seekers: the investors look for cheap factors - labor or/ and natural Resources This kind of FDI is mainly export oriented and the host country is rather seen as an export platform. They produce
11、what is named vertical integration (Helpman1984; Helpman and Krugman 1985). These classical or traditional reasons for investing abroad are complemented today with new reasons for becoming internationalized firms, such as capabilities, innovatory activities, participation in a cluster, social respon
12、sibility/moral ecology etc. (Dunning 2007b). Countries in Central and Eastern Europe generally offer certain attractive conditions, especially comparative lower labor costs, along with an educated and skilled labor force. Moreover, the fiscal regime has become very encouraging in many of these count
13、ries. They even compete to attract FDI. Consequently, important foreign investors preferred to re-localize completely or partly their activities or to open branches in these new areas. The ways of entering these economies are as follows: Full new investment (green field investment) As participant in
14、 the privatization process (brown field investment) By mergers and acquisitions of already existing private or state owned Companies. The choice of entry mode is an important decision for a company. A short synthesis of theories and empirical researches on this issue can be found in Xuemin and Decke
15、r 2004. What is obvious especially from empirical research is that not one single reason is taken into account when a company decides to invest abroad and to adopt a certain mode of doing it. Romania is one of the groups of CEECs which was lagging behind concerning the attractiveness of FDI for many
16、 years. The situation has changed and one may notice a new and positive trend to this respect. Our paper aims to reveal the contribution of main determinant factors to the evolution of one of the most relevant indicator that is FDI/GDP (%). The analyzes is based on data provided by UNCTAD, ERDB, Nat
17、ional Bank of Romania, and using SPSS for processing. Results allowed us to describe the contribution of main determinant factors, which have been extracted from a certain number of explicative variables. The paper is structured as follows. The first part is devoted to a short presentation of the ge
18、nerally accepted main FDI determinants, and of some specificity when it is about the new market economies such as those in the CEECs. The second part presents the research methodology and analyzes the results obtained by evaluation of the determinant factors contribution in the case of Romania. The
19、final part consists of our conclusions and of policy implications. FDI: Main Determinant Factors Several published syntheses of theoretical and empirical research (Andersen and Hainaut 1998; Lipsey 2002; Blonigen 2005) underlined that FDI is generally attracted by factors such as: market size, and i
20、ts potential development, factor costs, especially labor cost, but also human capital (education and skills), trade openness, infrastructure reform, price liberalization, fiscal policy, institutional development, technological absorption capacity, etc. The FDI determinants might be grouped into basi
21、c factors, which refer to primary comparative attractiveness conditions of host countries (size, geographical position), and complementary factors/determinants, which enforce or, contrary, weaken/reduce the attractiveness of a host country, i.e. it is about specific created country attractiveness (m
22、arket potential, labor force cost and skill, other factors cost, business climate, including institutional development). The combination of all these factors explains why MNCs decide to invest in a certain country, in a certain area. The simultaneously presence of certain determinants factors would
23、explain the pattern but also the size of FDI flow in a certain country. Predominance of one or other of the factors and motives for firms decision give a certain profile to the respective investment. Thus, the literature came to the already known traditional findings regarding the main types of fore
24、ign investment in the host countries (see Kazuhiko and Tomohara 2007): horizontal investment (market seeking), and vertical investment (efficiency seeking). The importance of one or other factors changes in time. For instance, during the first years of transition in the CEECs, political stability an
25、d macroeconomic stabilization, including institutional development, were premises for any interest for foreign investors (see, Baniak et al. 2002; Dunning 2007a). Along with the progress in political and economic transformations, and especially with the progress in fulfilling the criteria of adhesio
26、n to the EU, the comparative advantages of investing in these countrieslow labor cost but educated labor force, relative high growth rate and growing market potentialbecame the most important determinant factors that directed the FDI flows towards this area (Botric and Skuflic 2005). Re-locations we
27、re also registered quite frequently, especially in the production field of labor-intensive goods. It is worth mentioning that certain advantages are temporary in character (labor cost, resource availability), and may diminish in time.1 Since the firm competitive position depends increasingly on the
28、innovation and technical capacity of absorption, on human capital (education and skills), and on the existence of conditions for development competitive clusters innovatory activities (Dunning 2007b), new factors of attractiveness have to be more promoted. When one talks about the factors that expla
29、in the FDI orientation, there are two categories of explicative variables: the first one is made up of factors that constitute the potential attractiveness for a country; the second one is made up of concrete motives for a firms decision to invest. There is no borderline between the two approachesde
30、terminants and motives. Actually, the determinant factors (i.e. the attractiveness of the country) or part of them become reasons for companies decisions to invest. What differ are the methodologies of evaluation: country (location) attractiveness becomes stock of FDI or flow of FDI as dependent var
31、iables that are explained through several quantitative measurable explicative variables; the evaluation of firms motives to invest is based on survey and the firm perception on the respective determinants. Since not all determinants are measurable, and not all the determinant impacts can be captured
32、, the quantitative measures are sometimes complemented by qualitative evaluation. In our paper, we evaluate the correlation between the amount of FDI stock/GDP (%) and several factor determinants in the case of Romania. Data and Methodology The data we have used are those published by UNCTAD, World
33、Investment Report 2006, ERDB, Transition Report 2007, National Bank of Romania, Institute for Statistics in Romania. We have chosen the Inward Stock of FDI/GDP in percentage as the dependent (explained) variable for each year in the period 19912006, and as initial explicative variables those which m
34、ight generally have a certain impact on companies decision to invest (market size, factor costs, business climate). Moreover, certain variables are particularly important in the new market economies economic liberalization, enterprise reform and privatization. These variables are usually quantified
35、to analyze a countrys progress in the transformation of the economy (see, ERDB, Transitions Reports). The initial explicative variables we have chosen for the host country (Romania) are: GDP-percentage change in real terms; GDP/cap in dollars; population; gross average monthly earnings in economy (a
36、nnual average) percentage change; real earnings index; labor unit cost; change in labor productivity in industry (in percent); share of trade in GDP (in%); EBRD index of Fore and trade liberalization; EBRD index of large-scale privatization; EBRD index of infrastructure reform; EBRD index of price l
37、iberalization; EBRD index of enterprise reform. Since the data had different measuring units it was first standardized and then analyzed using SPSS 15.0. The number of initial variables is 13 (see, Appendix 1). Using the factor analysis method, the number of the initial variables was reduced to only
38、 four factors/determinants. The method allows us to see the degree of existing correlation between each variable and the respective factor (determinant), and to name the factors according to the highest correlation coefficients between explicative variable and each factor. For a better definition of
39、 each factor the Equifax rotation was used, consisting of six steps (iterations). The results are in Table 1. The withheld information represents 88.552% of the whole, considering as sufficient the retention of four factors. To put it differently, the four factors explain 88.552% of the variation of
40、 the chosen dependent variable (FDI/GDP %). Each variable is found on each one of the four factors. Contributions of the factor are: F1: 28.98%; F2: 21.8%; F3: 20%; F4: 17.764% In order to describe the main explicative factors, the extraction and iteration methods calculated the correlation coeffici
41、ents between each variable and the four determinant factors previously obtained. Taking into account the highest correlation Between each variable and every one of the four factors, the resulted picture is in Table 2. We went further with our analyzes and estimated the coefficients of a linear regre
42、ssion model in which the dependents variable is log FDI/GDP, in %, and the explicative variables are the four factors (which are the new generalized variables having as main characteristic the lack of auto-correlation). Since the resulted factors are linear combinations of the initial variables, the
43、 relation between all these variables can be modeled using a linear function. In order to validate the model, the following hypotheses have to be tested: 1. The significance of the coefficients in the model: Using the t test, P0.05, we may notice that all the coefficients in Table 4 are significant.
44、 2. The errors should be not correlated: To check this hypotheses, we used the DurbinWatson Statistic, DW = 1.943.Based on the critical values for the four repressors, a = 0.05, and a sample of size n = 16, the upper value limit is 1.93, and the lower value limit is 0.74. According to the theory we
45、may state that the errors are not correlated. 3. The absence of outliers: We look at standard residual and check whether the minimum and maximum values are more than 3. We do not have outliers in this case (see also Fig. 1). 4. Normal distribution of errors: If the errors follow a normal distributio
46、n, only 5% of standardized residuals (in absolute value) are higher than 2. Figure 1 suggests the existence of a rather normal distribution. The null hypothesis states that the errors are normally distributed. Applying the ShapiroWilkes (Table 5), we see that the null hypothesis cannot be rejected (
47、P0.05), either for standardized residuals or for student zed residuals. 5. Homoscedasticity of errors: The Scatter plot (Fig. 2), which has been build based on forecasted values and residuals, clearly shows that the values are distributed on both sides of the mean. There is no evident connection tha
48、t might explain the deviation from that mean. We may say that the variance of error is constant; therefore, the errors are homoscedastic. We have also used the student zed residuals (residual is divided to each case of estimated standard deviation). Unlike other types of residuals, values of the stu
49、dent zed residuals are not influenced by the values of the explicative variables. We may conclude that by testing the validity of the linear regression model in our case we demonstrated that the model is correct and expresses very well the relations between FDI/GDP% and the four factors. Significance of Results The significance of the four factors is as follows: Factor 1 is the most important, and may be named Market size and potential. The variables positively correlated with this factor are: GDP/capita which means purchasing power increasing; sh
