Geographic concentration in Portugal and regional specific factors

Transcription

1 MPRA Munich Personal RePEc Archive Geographic concentration in Portugal and regional specific factors Vítor João Pereira Domingues Martinho Escola Superior Agrária, Instuto Polécnico de Viseu 0 Online at MPRA Paper No. 7, posted 8. July 0 :6 UTC

2 Alert! This author has published many duplicate versions of very similar papers wh slightly different tles, but whout an appropriate notice. This may apply to this contribution, too. GEOGRAPHIC CONCENTRATION IN PORTUGAL AND REGIONAL SPECIFIC FACTORS Vor João Pereira Domingues Martinho Unidade de I&D do Instuto Polécnico de Viseu Av. Cor. José Maria Vale de Andrade Campus Polécnico 0-0 Viseu (PORTUGAL) ABSTRACT This paper pretends to analyze the importance which the natural advantages and local resources are in the manufacturing industry location, in relation wh the "spillovers" effects and industrial policies. To this, we estimate the Rybczynski equation matrix for the various manufacturing industries in Portugal, at regional level (NUTS II) and for the period 980 to 999. Estimations are displayed wh the model mentioned and for four different periods, namely 980 to 98, from 986 to 99, from 980 to 99 and from 99 to 999. The consideration of the various periods until 99, aims to capture the effects of our entrance at the, in that time, EEC (European Economic Communy) and the consideration of a period from 99 is because the change in methodology for compiling statistical data taken from this time in Portugal. As a summary conclusion, noted that the location of manufacturing in Portugal is still mostly explained by specific factors, wh a tendency to increase in some cases the explanation by these factors, having the effect "spillovers" and industrial policies ltle importance in this context. Keywords: geographical concentration; Portuguese regions; specific factors.. INTRODUCTION In this work, taking into account the work of Kim (999), seeks to analyze the importance of the natural advantages and local resources (specific factors of locations) have in explaining the geographic concentration over time in the Portuguese regions, relatively effects "spillovers" and industrial policies (in particular, the modernization and innovation that have allowed manufacturing in other countries take better advantage of posive externalies). For this, we estimated the Rybczynski equation matrix for the different manufacturing industries in the regions of Portugal, for the period 980 to 999. It should be noted that while the model of inter-regional trade, the Heckscher-Ohlin-Vanek, presents a linear relationship between net exports and inter-regional specific factors of locations, the Rybczynski theorem provides a linear relationship between regional production and specific factors of locations. In principle, the residual part of the estimation of Rybczynski, measured by the difference between the adjusted degree of explanation (R) and the un presents a approximated estimate of the importance not only of the "spillovers effects, as considered by Kim (999), but also of the industrial policies, because, industrial policies of modernization and innovation are interconnected wh the "spillover" effects. However, must be some caution wh this interpretation, because, for example, although the growth of unexplained variation can be attributed to the growing importance of externalies "Marshallians" or "spillovers" effects and industrial policies, this conclusion may not be correct. Since the "spillovers" effects and industrial policies are measured as a residual part, the growth in the residual can be caused, also, for example, by growth in the randomness of the location of the products manufactured and the growing importance of external trade in goods and factors. The designation of externalies "Marshallians" or "spillovers" effects, is because Marshall (90) have identified in a systematic way the causes of geographical concentration in industrial activies. Some recent works in these areas of thought, have sought to precisely identify solutions to these and other assumptions, present in some works, such as ()Krugman (99), ()Krugman (99), ()Krugman et al. (99), (6)Fuja et al. (999), (7)Matsuyama (99), (8)Gali (99) and other related wh spatial issues. It is also important to note that Marshall identifies the natural advantages as a major cause of geographical concentration (Kim, 999). Another classification for the causes of concentration was made by (9)Scovsky (9), in other words, this author made a distinction between technological externalies, materialized through interactions unrelated to the market that directly affect consumers' utily or production functions of companies and pecuniary externalies that result from market interactions, in the proportion that companies engage in trade of products.

3 Alert! This author has published many duplicate versions of very similar papers wh slightly different tles, but whout an appropriate notice. This may apply to this contribution, too.. THE MODEL THAT ANALYZES THE IMPORTANCE OF NATURAL ADVANTAGES AND LOCAL RESOURCES IN AGGLOMERATION According to Kim (999), the Rybczynski theorem states that an increase in the supply of one factor leads to an increased production of the good that uses this factor intensively and a reduction in the production of other goods. Given these assumptions, the linear relationship between regional output and offers of regional factors, may be the following: Y A V, where Y (nx) is a vector of output, A (nxm) is a matrix of factor intensies or matrix input Rybczynski and V (mx) is a vector of specific factors to locations. For the output we used the gross value added of different manufacturing industries, to the specific factors of the locations used the labor, land and capal. For the labor we used the employees in manufacturing industries considered (symbolized in the following equation by "Labor") and the capal, because the lack of statistical data, was considered until 99, as a "proxy", the production in construction and public works (the choice of this variable is related to several reasons including the fact that represents a part of the investment made during this period and symbolize the part of existing local resources, particularly in terms of infrastructure, because this has been considered from 99) and from 99 was considered also production in this sector and the gross formation of fixed capal in manufacturing. Wh regard to land, although this factor is often used as specific of thr locations, the amount of land is unlikely to serve as a significant specific factor of thr locations. Alternatively, in this work is used the prodution of various extractive sectors, such as a "proxy" for the land. These sectors until 99, include agriculture, forestry and fisheries (represented by "Agriculture") and production of natural resources and energy (symbolized by "Energy") and from 99 include agriculture and fisheries (represented by "Agriculture") the forest ("Forest"), extractive industry of metallic mineral products ("Extraction"), extractive industry of various products ("Extraction") and energy production ("Energy"). The overall regression is then used as follows: ln Y ln Labor ln Extraction ln Agricultur e ln Energy 6 ln Florestry ln Construction 7 ln Extraction ln Capal 8 In this context, is expected that there is, above all, a posive relationship between the production of each of the manufacturing industry located in a region and that region-specific factors required for this industry, in particular, to emphasize the more noticeable cases, between food industry and agriculture, among the textile industry and labor (given the characteristics of this industry), among the industry of metal products and metal and mineral extraction and from the paper industry and forest.. STATISTICAL DATA USED Taking into account the variables of the model presented previously, we used statistical data of the five temporal regions of mainland Portugal, from the regional database of Eurostat statistics (Eurostat Regio of Statistics 000) and INE (National Accounts 00). The data are relative to regional gross value added of agriculture, fisheries and forestry, extractive industry of metallic mineral products, extractive industry of various products, the industry of fuel and energy products, each of manufacturing industry and construction and public works. We used also data relating to employees in each of the manufacturing industries and gross formation of fixed capal.. THE ESTIMATES MADE In the estimates made were used panel data relating to the five regions of Portugal, for the years It is intended to estimate the Rybczynski equation matrix in the linear form presented earlier. In the results presented in the following tables, there is a strong posive relationship between gross value added and labor in particular in the industries of metals, mineral products, chemicals, equipment and electrical goods, food, textile, paper and several products (which in some industries, should not be checked). On the other hand, there is an increased dependence on natural and local resources in industries as the food and paper sectors. We found that the location of manufacturing industry is yet mostly explained by specific factors of locations, wh a tendency to increase in some cases and poorly explained by "spillovers" effects and industrial policies. It should be noted, finally, ltle correlation between the location of manufacturing industry and gross formation of fixed capal in different regions of mainland Portugal.

4 Alert! This author has published many duplicate versions of very similar papers wh slightly different tles, but whout an appropriate notice. This may apply to this contribution, too. Table : Results of estimations for the years lny ln Labor ln Agricultur e ln Energy ln Constructi on IMT IMI IPQ IEE IET IAL ITE IPA IPD (*)..0 (*) (0.6) (.) (0.) (-.07) (0.6) (.) Dummy (0.96) (.680) (0.8) Dummy (.) (.) (0.908) Dummy (.06) (.69) (.09) Dummy (.) (.9) (0.6) Dummy (.078) (.) (0.0) (*) (*) 0.7 (*) 0.9 (*).80 (*) 0.86 (*) (.68) (0.9) (-.09) (0.7) (-.) (.) (.88) (.8) (.089) (**) 0.9 (*) (0.90) (0.8) (0.67) (0.68) (-0.9) (0.0) (.7) (.79) (.0) (*) (0.) (0.99) (-0.0) (-0.6) (-0.6) (.07) (-.7) (-0.70) (-.) (*) 0. (**) (-0.8) (.6) (-0.88) (.0) (.) (.880) (0.70) (-0.79) (0.0) Sum of the elasticies R adjusted Residual part Durbin Hausman test. (a) (b)(*) 6.9 (a).07 (b)(*).077 (b)(*).6 (a).90 (a) (c) (c) For each of the industries, the first values correspond to the coefficients of each of the variables and values in brackets represent t-statistic of each; Estimation wh variables "dummies"; Estimation wh random effects; (*) coefficient statistically significant at % (**) Coefficient statistically significant at 0%; IMT, metals industries; IMI, industrial mineral;, IPQ, the chemicals industries; IEE, equipment and electrical goods industries; EIT, transport equipment industry; ITB, food industry; ITE, textiles industries; IPA, paper industry; IPD, manufacturing of various products; (a) accepted the hypothesis of random effects; (b) reject the hypothesis of random effects; (c) Amount not statistically acceptable. Table : Results of estimations for the years lny ln Labor ln Agriculture ln Energy ln Constructi on IMT IMI 0.00 (0.80) Dummy 8.7 (*) (.) Dummy 9. (*) (.7) Dummy 9. (*) (.6) Dummy 8.69 (*) (.6) Dummy (*).0 (*) (.96) 0.8 (.) 0. (.68) -.9 (*) (-.0) (.69) 0.7 (*) (.6) -0.8 (*) (-.0) -0. (*) (-.) 0.9 (*) (.69) IPQ -.67 (*) (-.) (*) (-.90) -. (*) (-.08) -.6 (*) (-.99) (*) (-.68).098 (*) (8.06) (*) (.68) 0.0 (0.7) 0.60 (.8) IEE. (*) (.8).99 (*) (.80). (*) (.80).0 (*) (.87).69 (*) (.6) 0.87 (*) (7.69) (-0.80) (-0.876) 0.06 (0.8) IET 9.8 (.60) 0.08 (**) (.766) 0. (**) (.797) 9.8 (.67) 7.60 (.77) 0.97 (*) (.) -0. (-0.9) 0.7 (0.8) 0. (*) (.066) IAL. (*) (.6) 0.78 (*) (.000) (-0.0) (-0.706) 0.66 (0.8) ITE.7 (*) (.6).90 (*) (.97).60 (*) (.).067 (*) (.67).06 (*) (.) (*) (.96) -0.8 (**) (-.9) -0.9 (**) (-.78) 0.9 (*) (.70) IPA 7.80 (*) (.6) 7. (*) (.00) 8.86 (*) (.).00 (*) (.6).696 (*) (.7) (-0.0) -0.7 (-0.0) -0.6 (-0.90) 0.7 (.96) IPD 8.0 (*) (.) 0.86 (*) (0.99) -0.8 (-0.780) -0. (*) (-.89) (-0.6)

5 Alert! This author has published many duplicate versions of very similar papers wh slightly different tles, but whout an appropriate notice. This may apply to this contribution, too. Sum of the elasticies R (c).87 (b)(*) 6.70 (b)(*).00 (b)(*) 9.70 (b)(*) (c).9 (b)(*) 6.9 (b)(*).08 (a) Table : Results of estimations for the whole period lny ln Labor ln Agricultur e ln Energy ln Constructi on adjusted Residual part Durbin- Hausman test IMT IMI IPQ IEE IET IAL ITE IPA IPD (**) (.06) (-.8) Dummy.86 (*) (6.68).00 (*) (.769) 7.0 (.88) 6.7 (*) (.8) -0.0 (-0.00).998 (*) (.87).6 (*) (.7) Dummy. (*) (6.79).7 (*) (.77) 8.67 (.80) 6.0 (*) (.798) (-0.00).87 (*) (.8).7 (*) (.78) Dummy.90 (*) (6.6). (*) (.87) 8.8 (.) 6.68 (*) (.86) -0.7 (-0.0).67 (*) (.0).7 (*) (.6) Dummy.9 (*) (6.8).9 (*) (.00) 7. (.9).7 (*) (.98) 0.0 (0.0) 9. (*) (.9) (*) (.) Dummy.86 (*) (6.77).08 (*) (.8).9 (0.8).997 (*) (.07) -.6 (-0.6) 8.87 (*) (.).77 (*) (.). 0. (*) (*) 0.7 (*) (*) 0.86 (*) (*) (8.880) (.87) (.) (7.67) (0.68) (.8) (.6) (0.7) (.6) (*) (.608) (-.) (.698) (-0.67) (-0.706) (0.077) (0.00) (0.78) (.09) (*) (*) (0.08) (-.86) (.) (-.76) (0.66) (-0.) (-.08) (0.009) (-.8) (*) (*) (-.99) (.6) (0.) (0.867) (.069) (.) (.) (0.) (-.8) Dummy (0.67) 0. (*) (.67) (-.00) 0.0 (0.68) 0. (0.89) (-0.) 0.0 (*) (.) 0.6 (*) (.76) 0.00 (0.) Sum of the elasticies R adjusted Residual part Durbin Hausman test (c) (b)(*) (c) (b)(*) 0.96 (b)(*) 7.67 (b)(*) (c). (b)(*) 6.97 (b)(*) ln Y ln Extraction Table : Results of estimations for the whole period ln Labor ln Agricultur e ln Energy 6 ln Florestry ln Construction 7 ln Extraction ln Capal 8 Dummy IMT.76 (0.6) IMI. (0.0) IPQ (-.7) IEE 6.66 (*) (.6) IET 7.0 (0.9) IAL ITE IPA IPD Dummy Dummy Dummy -.7 (-.70) -. (-.86) (0.66) (-0.90)

6 Alert! This author has published many duplicate versions of very similar papers wh slightly different tles, but whout an appropriate notice. This may apply to this contribution, too. Dummy.9. (*) (*).0 (*) 0.8 (**) (7.66) (.89) (.9) (-0.) (0.60) (0.) (.7) (.887) (.) (*) (**) 0.08 (**) (0.778) (-0.) (.99) (-.6) (-0.70) (.996) (.9) (-.666) (-0.) (**) 0.98 (*) 0.76 (*) 0.8 (**) (-.70) (-.68) (.09) (-.769) (-0.) (.0) (6.7) (.689) (.7) (**) 0.07 (*) (-.0) (-.07) (0.9) (-.7) (-0.) (.6) (.7) (0.) (-.0) (*) 0. (*).98 (*) -.09 (*) (**) (.89) (.86) (.7) (-.9) (0.80) (0.07) (-.79) (-.6) (0.09) (*) (-.80) (-0.7) (-.96) (.8) (0.0) (-.99) (-6.689) (-0.6) (-.0) (-.7) (-.7) (0.7) (.) (0.6) (-0.6) (.60) (.88) (.6) (**) (**) (*) (-.8) (.0) (.0) (.) (0.96) (0.) (7.0) (-0.997) (-0.87) Sum of the elasticies R adjusted Residual part Durbin Hausman test (c) (c) (c) (c) (c) (c) 6.06 (b)(*) 8.0 (b)(*) (b)(*). SOME CONCLUSIONS Analyzing the results of the estimations made appears that there is a strong posive relationship between gross value added and labor, particularly in the industries of metals, mineral products, chemicals, equipment and electrical goods, food, textile, paper and several products, which in fact is proved by the statistical analysis. On the other hand, there is an increased dependence on natural and local resources in industries, as the food and paper firms. About the existence of economies to scale or not, ltle can be concluded by the values obtained from the sum of elasticies. On the other hand, our entry into the EEC had ltle effect on the Portuguese manufacturing industry, what must be a matter for reflection. In short, be noted that the location of the Portuguese manufacturing industry is still mostly explained by specific factors of locations, wh a tendency to increase in some cases, capal has ltle influence on this location and the industrial policies of modernization and innovation are not relevant, especially those that have come from the European Union, what is more worrying. 6. REFERENCES. S. Kim. Regions, resources, and economic geography: Sources of U.S. regional comparative advantage, Regional Science and Urban Economics (9), - (999).. A. Marshall. Principles of Economics. McMillan 90.. P. Krugman. Increasing returns and economic geography. Journal of Polical Economy (99), 8-99 (99).., P. Krugma. A dynamic spatial model. NBER Working Paper P. Krugman and A. Venables. Globalization and the inequaly of nations. Quarterly Journal of Economics (0), (99). 6. M. Fuja; P. Krugman; and A. Venables. The Spatial Economy. Cies, Regions and International Trade. MIT Press, Cambridge MA K. Matsuyama. Increasing returns, modernization, and indeterminacy of equilibrium. Quarterly Journal of Economics (06), (99). 8. J. Galì. Local externalies, convex adjustment costs, and sunspot equilibria. Journal of Economic Theory (6), - (99). 9. T. Scovsky. Two concepts of external economies. Journal of Polical Economy (6), - (9).