Empirical analysis of external economies and S-C-P paradigm

Transcription

1 Local and Industrial Development Module A - 7 Empirical analysis of external economies and S-C-P paradigm draft version of M.Bellandi, M. J. R. Fuensanta (2010 ). An Empirical analysis of district external economies based on a structure-conduct-performance framework, Papers of Regional Science, vol. 89:4 (pp ) 1

2 Empirical analysis on LID cases, in particular on IDs - Approximate empirical identification of regional clusters or of local systems hosting industrial development - Methods of empirical investigation - In particular: statistical methods for the identification of presence of ID effects (i.e. the strength of ID external economies) - Example: the application of econometric analysis based on a S-C-P framework to a set of Spain IDs 2

3 Approximate empirical identification Two types of methods of identification: a) Cluster based methods - U.S. Cluster methodology (Porter et al. 2014) - Simplified EU methodology - Case based check or identification (like in India) b) Place based methods See next slides - Methods based on identification and characters of local systems - Case based check or identification 3

4 Local labour system or TTWA (travel to work area) An approximate spatial identification of a local system has been defined by F. Sforzi (for example Sforzi 1997), and is now adopted by Istat (the Italian National Institute of Statistics). It is based on data concerning daily commuting from home to job location. This data are collected at an infra municipality level within the national Census, each ten year. The methodology by Istat Sforzi is aimed to find sets of contiguous municipalities. Each set has to show a high degree of inclusion of the commuting inflows and outflows based on the municipalities of the same set (more than 75%). A real local system is a place where a community of people lives and works, with a great deal of persistently overlapping experiences; possibly it corresponds to a set of contiguous towns, villages, rural areas, with a principal town or city 4

5 From TTWA to stat. IDs Criteria for qualifying a TTWA as a an ID: 1- Manufacturing specialization in terms of employment against national average (E for Employment; GB for national average) 2- Composition of firms in the TTWA in terms of size; in particular whether the TTWA is dominated by small or medium size firms. 3- Presence of one or more TTWA s main sectors, by means of two indicators: a location quotient and a prevalence index. 4- Combination of firms size and industrial specialization so as to clarify whether the sector(s) in which a certain area is specialized is (are) characterized by small to medium sized firms. 5

6 Comparison between Ids in Spain (2001), Italy (1996), and UK (1997) From table 4 in Rafael boix and Vittorio Galletto, MAPPING MARSHALLIAN INDUSTRIAL DISTRICTS IN SPAIN, Paper presented to the EUNIP International Conference 2006, June University of 6 Limerick

7 Industrial districts in Italy, year 2001 Istat (su 685) nel

8 Industrial districts in Spain. Adapted ISTAT methodology. Year 2001 Rafael Boix y Vittorio Galletto, Sistemas Locales de Trabajo y Distritos Industriales Marshallianos en España, in Economia industrial, no. 359,

9 INDUSTRIAL DISTRICTS IN UNITED KINGDOM, YEAR 1997 De Propris, L., Mapping Local Production Systems in the UK: Methodology and Application, Regional Studies, Vol. 39.2, p

10 Case based check or identification a) In-depth investigation of the characters of the clusters, aimed at identifying its structural and dynamic features (recall topic 5, slide 5 p. 9) - size and number of specialized firms running complementary activities within the main sectors and the complementary ones (business clusters) - market and non market mechanisms for relations among local firms - local fabric of social and civic life supporting the main cluster, presence of local private leaders, joint action, strategic public action in the cluster. Other social and civic features in the locality - processes of local development based on the cluster: historical genesis of the cluster, relation with the characters of the locality, and possible transition points in the past b) Strengths and weaknesses, risks and opportunities. 10

11 Steps of in-depth investigation: characters of the ID s main clusters types of firms (ownership and management); types of products, production processes, flexibility and quality control; distribution of size, presence of leaders, how dominant? local horizontal and vertical linkages, subcontracting; local and external markets and marketing channels; sources of innovations. 11

12 Steps of in-depth investigation: ID s historical genesis When and how did the specialized production start? Who were the leading actors during the take-off? What have been the characteristics of the evolution after the take-off? - Smooth growth with quantitative expansion - Smooth enlargement of the division of labor, in the quality of products and in the access to national and international markets - Crises and turning points, what their content, How do they combine with the evolution/crises of other clusters in the same ID 12

13 Steps of in-depth investigation: Collective action and social features Institutional framework (collective standards and conventions at the local level, combination with upper level rules and law); Types and quality of job, wages, training, unemployment, enployees by gender, migrant workers; Intermediary organisations and their services (private joint action); Entrepreneurs playing as social leaders; Public support (ordinary and strategic) to the industry and to the social and environmental life of the district (minum pages, welfare, etc.); Policies from external agencies (e.g. state government, multinationals); Composition of the various types of strategic action (governance and social dialogue); Entrepreneurial and trust attitudes; local know how. 13

14 Steps of in-depth investigation: SWOT Strengths and Weaknesses Costs and productivity of labor and resources Quality of products and innovation Access to the markets and finance Collective support and infrastructure Opportunities and Threats Challenge from new competitors, changing role of big firms Environmental or social limits to growth Access to new markets, new ways of internalizing innovation, and new upper level rules 14

15 Statistical methods for the identification of presence of ID effects - District effect: econometric analysis of the superior performance of firms located in IDs with respect to firms located in other places, possibly in the same sectors (clusters); - Local factor analysis: econometric analysis of the relevance of single factors possibly related to the generation of district external economies in a set of IDs; - Cluster and network analysis of main industrial and social components within an ID and their local and extra-local relations - Econometric analysis of the main processes within IDs in a set, which allow for a more or less extensive realization of external economies within the same IDs a district context defined in a synthetic but holistic way. In particular (in what follows from slide p. 17: Structure-Conduct-Performance (SCP) framework, following a theoretical model of external economies 15

16 The statistical measure of the district effect Returns on equity and investments, for (non micro) firms in Italy, within and outside industrial districts [199 IDs according ISTAT 1991]. Years L.F. Signorini e M. Omiccioli, L indagine della Banca d Italia sui Distretti Industriali, in IPI, L esperienza italiana dei distretti industriali, Roma, 2002, pp

17 Econometric analysis based on a SPC framework -1 SPC framework on the generation of an ID s external economies S basic S io C m P v Source: adaptation from Bellandi, M. (2002). Italian industrial districts: an industrial economics interpretation, European Planning Studies, 10:4 S pg C st P e Symbol P v P e C m C st S basic S io S pg Abbreviation for Performance, value Performance, external (economies potential) Conduct, market (firms) Conduct, constructive action (by private and public leaders) Structure, global and local basic conditions Structure, industrial organisation Structure, specific public goods (deliberate) 17

18 SPC framework - 1 Structure variables S io : structural aspects corresponding to some ID features of the main local cluster, i.e. a high concentration of firms predominantly of small and medium size, a high level of sectoral specialization, availability of local specialised suppliers, density of entrepreneurs, proportion of employment in the principal industry; etc. S pg : availability of specific public goods, in particular those which are provided or supported by deliberate action (as opposed to those incorporated in local customs and conventions); S basic : structural attributes which influence the opportunity set of ID agents, in terms of choices and rewards, but which, nevertheless, are only weakly and slowly influenced in an evolutionary way by what cluster agents do at both the individual and aggregate level while S io strictly refers to the main cluster of producers, other aggregate aspects of the industrial structure of the district are to be incorporated as part of S basic 18

19 SPC framework - 2 Conduct variables C m : conduct of the agents operating inside the ID (main cluster and other components). It concerns business strategy and embraces decisions concerning the internal organization of production (product diversification, increase of production capacity, investment in fixed assets, etc.), the R&D activities and intensity, and/or the formation of cooperative agreements with other companies and institutions located within the district. Performance variables P v : performance of individual firms belonging to the district's main industry. It may be seen as depending on: a) internal sources of production and trade efficiency, and b) efficiency sources linked to the capacity of the firms to embed themselves in the industrial and social context of the district. Indeed, this second type of sources identifies the effect of district external economies on performance, i.e. P e within the framework 19

20 SPC framework - 3 Relations / 1 - The potential external economies (P e ) depend both on S io and S pg. The translation of this potential into business value (P v ) depends on appropriate market conducts (C m ) and is also influenced by S basic - Within a ID cluster, the value generated by performance may feedback fruitfully on S io. - C m does not necessary bring to a re-investment of individual returns in ways which strengthen S io features. - However, a direct relation may be explained in terms of realized expectations: i.e. a high degree of proximity of the industrial structure of the cluster to ID features is also built on the expectation that those district enterprises which adopt conducts consistent with the access to district external economies will benefit from a higher value. So that, when this high value is realized, expectations are not contradicted. 20

21 SPC framework - 4 Relations / 2 - S io is directly constrained both by S pg, as an ID industrial structure needs the support of a robust architecture of specifically built public goods, and by basic structural conditions (S basic ), such as the type of sector of specialization or the type of region of localisation; - The provision of specific public goods (S pg ), in particular those more directly influenced by constructive (public and collective) strategies and actions, depends on various conditions too; - On the one hand, the presence of district features in the past may have favoured deliberate constructive actions by public and collective agencies aiming at a stronger provision of S pg ; - On the other, a direct relation with realized value (P v ), which is the local funding basis of S pg, may be explained as above in terms of realized expectations; - An important role is played by basic structural conditions (S basic ), e.g. those expressing social and political cohesion at the local level. 21

22 Econometric analysis based on a SPC framework: application 1 from Bellandi-Fuensanta All the relations considered together, apart from the feedbacks to basic structural components which would require long run and evolutionistic methods of analysis; - A higher or lower degree of proximity of intermediate structural components, such as Sio or Spg, to ID general features may be related to the realization of higher or lower levels of value produced by the local enterprises, showing the relevance of ID external economies both directly and indirectly, in the latter case through feedbacks; - Levels of value and the degrees of proximity may be influenced also by various basic structural characters and conditions, which are not related to the ID nature per se, but to other dimensions of the identity of each district, like sectors of specialization, etc. - In case: 45 IDs located in Castilla-La Mancha (years ) 22

23 Econometric analysis based on a SPC framework : application 2 - Since each component of the SPC framework above includes an open list of specific characters, and most of them are difficult to be measured directly with available statistical data, the quantitative application needs the selection of proxies and their aggregation in various types of indexes with various types of statistical methods see paper table 1 Description of variables and sources of data - A general model of the main loops of district external economies 1g) District features of industrial organization equation Sio = f1[pv, Sio-1, Spg, Sbasic-local (GROWTH), Sbasic-global (PAVITT)] 2g) Public goods from constructive action equation Spg = f2[pv, Sio-1, Sbasic-local (CIVIC and POP), Sbasic-global (CREDIT)] 3g) Performance related to district features equation Pv = f3[(sio, Spg, Sbasic-local (SIZE and SERVICES), Sbasic-global (COYUN)] see paper tables 3 and 4 on the analytic form of the general model as a simultaneous equation system and its reduced form 23

24 Econometric analysis based on a SPC framework: application 3 - The three endogenous variables: S io, S pg, and P v. - The other endogenous components (C m, C st, and P e ) cannot be taken into account directly, since direct measures of them are very difficult to obtain: their influence may be detected indirectly. - The exogenous variables are expression of both lagged feedbacks (S io -1) and S basic local and global conditions, and correspond to the other measures and indexes of the data set - S io equation incorporates three exogenous predictors: Sio-1structural characteristics of the district s main cluster in a previous period, in particular the year 1999; GROWTH measures the growth of the manufacturing industry in the district, and it influences strongly the expectations of district agents on the profitability of investing in the district structure; PAVITT, a dummy variable that indicates the technological regime, in particular whether the district s principal industry belongs to the Pavitt category of suppliers-dominated 24

25 Econometric analysis based on a SPC framework: : application 4 - S pg equation incorporates three other exogenous predictors: CIVIC, an index which measures the level of local civic participation, related to local social capital, which includes aspects such as associationism and involvement in public affairs; POP, a more generic predictor of willingness to cooperate of district actors, i.e. the population size: a larger population increases the possibilities for both interaction and development of cooperative arrangements; but, as the size of the industrial district gets larger, the bonds that keep district inhabitants together become weaker, CREDIT, the measure of the number of bank branches located in the ID, a proxy for the degree of diversification and competition of the local bank structure, and therefore, for the existence of a good access to banking services in the district; however an easier access to external finance may act as a disincentive for the optimal management of the production process. 25

26 Econometric analysis based on a SPC framework: : application 5 - P v equation incorporates three last exogenous predictors: - SIZE a variable which measures the total employment in the district: the larger the size of the economic activity in the district, the greater the opportunities will be for the emergence of local synergies; however, an increase in size can bring agglomeration diseconomies; - SERV represents the relative importance of the presence business services (technology and information services, R&D, or accounting, advertising, and legal services, etc.): ID external economies contributing to P v may come not directly from the main cluster, but from the network of complementary or subsidiary activities which have not been included in the statistical definition of the main cluster. - COYUN, expression of the influence of basic external conditions as the general situation of the industry in the country, on performance : here approximated by an index of the extent to which a region is specialized in those industrial sectors which, on a national basis, are experiencing the largest growth or, on the contrary, which are stagnant. 26

27 Econometric analysis based on a SPC framework: results 1 - The results obtained illustrate the feasibility of an econometric model built for applying an adapted SCP framework to ID conditions; - Single empirical results concerning 45 IDs in Castilla-La Mancha ( ) should not be considered as definitive, however they show some interesting inferences. 1) The performance of ID firms seems not be influenced in aggregate by either industrial structure or by public goods supply. It has, however, a significant effect on the pattern of industrial organization, strengthening the degree of districtuality of the system; 2) The size of an ID is a factor that affects the reproduction of the competitive advantages associated with it; it seems that also in the IDs of Castilla-La Mancha the medium-sized urban areas are the more propitious to host robust district processes; 3) Efficiency (P v ) exerts a negative effect over the industrial district s endowment of public goods. The cooperative behavior of district actors tends to be activated only when economic efficiency is declining; 27

28 Econometric analysis based on a SPC framework: results 2 - Follows on results concerning 45 IDs in Castilla-La Mancha ( ): 4) But the civic attitude of the local community exerts a positive effect on the efficiency of district firms (concept of social capital); 5) The expansion of overall manufacturing employment of the ID (GROWTH) has a negative impact on S io (the district-like structure of the local industry), suggesting that it tends to be associated, in this sample, not to the growth of the main industry, but to the emergence of new industries (probably new SMEs clusters) in the ID. 6) So, transformation and transition processes may affect the industrial districts under observation, as supported by the sign and significance of the employment growth variable. 7) This result is worth exploring further since this knowledge can be essential to the adoption of public policies which could help to prevent the deindustrialization of formerly prosperous areas and which would also secure stability in economic restructuring processes