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Regional Studies
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Structural Changes in Less Developed Areas: An Input- Output Framework Claudia Ciobanua; Konstadinos Mattasa; Dimitris Psaltopoulosb a Department of Agricultural Economics, Aristotle University of Thessaloniki, Thessaloniki, Greece b Department of Economics, University of Patras, Patras, Greece Online publication date: 18 August 2010
To cite this Article Ciobanu, Claudia , Mattas, Konstadinos and Psaltopoulos, Dimitris(2004) 'Structural Changes in Less
Developed Areas: An Input- Output Framework', Regional Studies, 38: 6, 603 — 614 To link to this Article: DOI: 10.1080/003434042000240914 URL: http://dx.doi.org/10.1080/003434042000240914
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Regional Studies, Vol. 38.6, pp. 603–614, August 2004
Structural Changes in Less Developed Areas: An Input–Output Framework CLAUDIA CIOBANU*, KONSTADINOS MATTAS* and DIMITRIS PSALTOPOULOS† *Department of Agricultural Economics, Aristotle University of Thessaloniki, PO Box 225, GR-54 006, Thessaloniki, Greece. Email:
[email protected] †Department of Economics, University of Patras, University Campus, Rio, GR-26 500, Patras, Greece
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(Received July 2002: in revised form December 2003) C C., M K. and P D. (2004) Structural changes in less developed areas: an input–output framework, Regional Studies 38, 603–614. This paper uses an input–output framework to investigate structural changes within a time span of 17 years in the regional economy of East Macedonia and Thrace in North East Greece, which has gone through considerable changes after Greece’s accession to the EU in 1981. The Generation of Regional Input–Output Tables procedure is followed for the construction of the relevant regional models. Then, changes in the structure of the regional economy are estimated using a series of indicators and structural decomposition analysis. Results reveal that between 1980 and 1997, the economy of the selected region has undergone significant transformations affecting both producing and consuming sectors. Also, final demand effects on gross production were more important than changes in technical coefficients, while employment requirements were significantly reduced. Finally, empirical findings provide an indication of the future trends in the structure of the regional economy. Input–output analysis
Changes
Economic structure
Region
Indicators
Agricultural sectors
C C., M K. et P D. (2004) Des changements structurels des zones en voie de de´veloppement: un tableau d’e´changes interindustriels, Regional Studies 38, 603–614. Cet article cherche a` employer un tableau d’e´changes interindustriels afin d’examiner des changements structurels sur une pe´riode de 17 anne´es pour ce qui est de l’e´conomie re´gionale de la Mace´doine de l’est et de la Thrace, situe´e dans le nord-est de la Gre`ce et qui a subi de profondes transformations depuis l’entre´e de la Gre`ce dans l’Ue en 1981. On suit les de´marches d’usage quant a` la production des tableaux d’e´changes interindustriels afin de construire des mode`les re´gionaux correspondants. A partir d’une se´rie d’indicateurs et d’une anlyse par de´composition structurelle, on estime les changements de la structure de l’e´conomie re´gionale. Les re´sultats laissent voir que, de 1980 a` 1997, l’e´conomie de la re´gion en question a subi de profondes transformations qui touchent non seulement les secteurs qui produisent, mais aussi ceux qui consomment. En outre, les effets de la demande finale sur la production brute se sont ave´re´s plus importants que le changement des coefficients techniques, alors que les offres d’emploi se sont sensiblement re´duites. Finalement, des preuves empiriques indiquent les tendances futures quant a` la structure de l’e´conomie re´gionale. Tableau d’e´changes interindustriels Secteurs agricoles
Changements
Structure e´conomique
Re´gion
Indicateurs
C C., M K. und P D. (2004) Struktureller Wandel in weniger entwickelten Gebieten: ein Aufwand-Ertragsmodell, Regional Studies 38, 603–614. Dieser Aufsatz benutzt einen Aufwands-Ertragsmodellrahmen zur Untersuchung von strukturellem Wandel in einem Zeitraum von 17 Jahren in der Regionalwirtschaft von Ostmazedonien und Thrakien in Nordostgriechenland, die sich seit dem Beitritt Griechenlands zur EU im Jahre 1981 betra¨chtlich gewandelt hat. Die Erstellung regionaler Aufswands-Ertragstabellen dient zur Konstruktion relevanter Regionalmodelle. Danach werden Vera¨nderungen in der Struktur der regionalen Wirtschaft mit Hilfe einer Indikatorenserie und einer Strukturzerlegungsanalyse berechnet. Die Ergebnisse zeigen, daß die Wirtschaft der betroffenen Region im Zeitraum 1980–97 signifikante Vera¨nderungen durchgemacht hat, die sowohl die Produktions-wie auch die Verbrauchersektoren betreffen. Es zeigt sich auch, daß Endnachfrageauswirkungen auf die Bruttoproduktion wichtiger waren als Umstellungen in technischen Koeffizienten, wa¨hrend Bewerbungen fu¨r Arbeitspla¨tze deutlich zuru¨ckgingen. Schließlich liefern empirisiche Befunde einen Anhalt fu¨r zuku¨nftige Tendenzen in der Struktur der regionalen Wirtschaft. Anfwands-Ertragsanalyse Umstellungen Landwirtschaftliche Sektoren
Wirtschaftsstruktur
Region
0034-3404 print/1360-0591 online/04/060603-12 ©2004 Regional Studies Association http://www.regional-studies-assoc.ac.uk
Indikatoren
DOI: 10.1080/0034340042000240914
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C C., M K. y P D. (2004) Cambios estructurales en a´ reas menos desarrolladas: un marco de input–output, Regional Studies 38, 603–614. Este artı´culo utiliza un marco de input–output para investigar cambios estructurales durante un periodo de 17 an˜ os en la economı´a regional de Macedonia del Este y de Tracia en el Noroeste de Grecia, la cual ha experimentado considerables cambios a partir de la entrada de Grecia en la Unio´ n Europea en 1981. Se sigue el procedimiento de Generacio´ n de Tablas Input–Output regionales para la elaboracio´ n de los modelos regionales relevantes. A continuacio´ n se estiman cambios en la estructura de la economı´a regional utilizando una serie de indicadores y un ana´ lisis de descomposicio´ n estructural. Los resultados muestran que, entre 1980 y 1997, la economı´a de las regiones seleccionadas experimento´ transformaciones significativas que afectaron tanto a los sectores de produccio´ n como a los de consumo. Adema´ s, los efectos finales de la demanda en la produccio´ n en bruto fueron ma´ s importantes que los cambios en los coeficientes te´ cnicos, mientras que los requerimientos de empleo se redujeron significativamente. Por u´ ltimo, los resultados empı´ricos proporcionan un indicativo sobre las futuras tendencias en la estructura de la economı´a regional. Ana´ lisis input–output
Cambios
Estructura econo´ mica
Regio´ n
Indicadores
Sectores agrı´colas
JEL classifications: R10, R15, Q10, Q18
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INTRODUCTION Structural economic change, defined as temporal changes in interactions among economic sectors ( J et al., 1990), can be studied via the use of various measures. The identification of methods that estimate sectoral interdependence is an important issue in development planning, as policy-makers prefer to ‘target’ sectors with comparatively high interindustry links, which in turn can facilitate an extensive round of economy-wide effects triggered by changes in final demand (D, 1974). A popular and effective way of analysing structural changes over time is the use of an input–output (I–O) framework because of its uniquely rich representation of economic structure (C, 1980; R and M, 1989). Within this context, structural decomposition analysis provides an analytical tool for distinguishing among major sources of change in an economy (R and C, 1991; R and C, 1996). The present paper applies an I–O approach to the intertemporal analysis of structural changes in the regional economy of East Macedonia and Thrace (EMT) – a NUTS 2, less developed area of the European Union, that is classified as ‘Objective 1’. To perform the relevant comparative analysis, I–O tables constructed for 1980 and 1997 were used. In this respect, one of the most widely used techniques for the construction of regional I–O tables, the ‘hybrid’ Generation of Regional Input–Output Tables (GRIT) procedure, is employed to generate the relevant regional models. Then, various indicators are used to measure the structural changes in the regional economy of EMT, which reveal the characteristics of the development process in the region. Knowledge of these measures is of interest to policy-makers in determining the development prospects of the region. The paper is organized as follows. A brief description of the region’s economy is presented in the second section, while the third section describes the measures employed to investigate structural changes in an economy. The fourth section deals with the results of
the structural analysis. Finally, concluding remarks are presented in the fifth section. THE REGION UNDER STUDY Based on systematic analyses on the evolution of regional inequalities in Greece since the 1980s (M et al., 1996; G et al., 1997; P and S, 2000), the peripheral region of EMT – located in the north-eastern part of Greece and consisting of five Prefectures (Drama, Kavala, Xanthi, Rodopi and Evros) – has been associated with a significant course of development and convergence. The convergence process is particularly interesting for less developed regions of Europe and especially those classified as ‘Objective 1’ because it illustrates the possibility of closing the gap between prosperous and less-developed regions of the European Union in a relatively short time, leading to the longterm policy objective of economic cohesion.1 Statistical data show that the EMT gross regional product per capita increased from 64.5% (1971) to 123.1% (1996) of the per capita Gross National Product, as the region developed more rapidly than any other region in Greece. An important role of this trend seems to originate from structural policy funds (active for many years in the region), which have been spent on agricultural infrastructure, including land reclamation, roads, irrigation and support for cooperatives (K et al., 1999). Table 1 provides some recent indicators of the economic structure of the EMT region in comparison with Greece. The region possesses 10.6% of total Greek agricultural area and 29.5% of its overall land and accounts for 5.3% of the national population. In terms of employment, the region has a greater share of employment in agriculture (40%) and a lower share of employment in manufacturing (17.9%) and services (42.1%) compared with the national level. The unemployment rate of EMT (8.3%) is below the Greek average (9.6%). As EMT continues to modernize, it may experience higher unemployment rates given the
Structural Changes in Less Developed Areas: An Input–Output Framework Table 1. Regional profile, 1997
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East Macedonia and Thrace Total area (km2) Agricultural area (km2) Population Employment Agriculture (%) Manufacture (%) Services (%) Unemployment rate (%) Labour productivitya (European Unionó100) Gross Domestic Producta (million drachmas) Agriculture (%) Manufacture (%) Services (%) Gross Domestic Product per capitaa (PPS)b (European Unionó100) Firm size in industry, small industry and construction Number of manufacturing firms (more than ten persons) Turnover (million drachmas)
Greece
14 145 4186 561 632 230 218 40.0 17.9 42.1 8.3
131 957 39 422 10 498 838 3 853 335 19.8 22.5 57.7 9.6
56.0
72.0
1 189 857 19.0 24.5 56.5
26 554 500 8.5 21.0 70.5
61.0
68.0
260 263 036
5407 6 315 029
Source: E (various years); E C (1999). Notes: a Data refer to 1996. b PPS, Purchasing Power Standard, is an artificial common currency that equalizes the purchasing power of different national currencies.
high share of population that is still employed in agriculture (I and P, 2000). On the other hand, the labour productivity in the region (56%) is quite far from the national level (72%), which reflects the problematic performance of the region. The region produces 4.5% of the Greek Gross Domestic Product (GDP). Nonetheless, with a per capita GDP of about 61% of the European Union average (compared with the Greek average of about 68%), EMT is included among the poorest regions of the European Union. However, compared with other regions of Greece, it is classified somewhere in the middle (K and S, 1998). In terms of the sectoral distribution of EMT’s GDP, agriculture is considered as an important sector (19% of total GDP in 1996), while manufacturing and services account for 24.5 and 56.5%, respectively, in the same year. The corresponding national figures are 8.5, 21.0 and 70.5%, respectively. Nine per cent of Greek agricultural output and 16% of the national production of cereals is produced in the region. Wheat, cotton, tobacco and tomato are amongst the main cultivations. The small size of the agricultural holdings, the comparatively high cost of agricultural inputs, the lack of technical support, the low level of farm skills and shortcomings in infrastructure are factors that contribute to low productivity
605
in local agriculture (A, 1990). Although the relative importance of the agricultural sector to the regional economy is expected to decline in the near future, agriculture is expected to remain an important source of income and employment (B, 1998). The region’s industrialization is quite recent, as most enterprises were established after 1970. The main economic stimulus originates from construction (dams for hydroelectric power, oil deposits, geothermal fields, non-ferrous material, marble, sulphurous composites) and manufacturing (food and beverages, textiles, clothing and footwear, furniture and metal products), which accounts for 260 firms and a gross output of 263 036 million drachmas (Table 1). The tertiary sector constitutes a significant source of economic activity for the region, with the majority of firms specializing in wholesale and retail trade, tourism, transport and communications. Other expanding service sectors in the region include banking, insurance, public administration, education and health. Public investment for improvements in infrastructure and incentives for the establishment and modernization of firms in all three sectors have supported the development of the region in the last two decades. Since 1986, development frameworks that have been applied in the region include the Integrated Mediterranean Programmes (1986–94), the Regional Development Programme and the Sectoral Programmes of the First (1989–94) and Second (1994–99) Community Support Framework, and the Community Initiatives such as ENVIREG (1989–94), INTERREG I (1989–94) and II (1994–99), and LEADER I and II. At present, regional policy support in EMT is mostly provided by the Sectoral and Regional Development Programmes of the Third Community Support Framework, while the main development objective is to promote the diversification of the regional economy.
METHODOLOGY AND DATA Regional input–output modelling The formalized approaches to the construction of regional I–O tables range from methods that include a considerable survey element to methods based completely on published data. The terms ‘survey’ and ‘nonsurvey’ suggest the existence of two well-defined and mutually exclusive groups, but in practice virtually almost all I–O tables are ‘hybrid’ ones, constructed by semi-survey techniques and employing primary and secondary sources to a greater or a lesser extent (R, 1983). Probably the most advanced of these techniques is the GRIT technique originally developed by J et al. (1979). In the present paper, the GRIT technique was used to generate regional I–O tables both for 1980 and 1997, which in turn were used to estimate various
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indicators of structural changes.2 The GRIT method estimates the regional intersectoral flows by applying an employment-based Cross Industrial Location Quotient to corresponding elements of the national matrix.3 After deriving initial estimates of regional technical coefficients, the GRIT procedure allows for the insertion of superior information, as judged by the analyst, to replace mechanically derived estimates. The superior data can come from survey data, published statistics and other sources (C and M, 1969; P and T, 1993; P, 1995).
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Measurements of structural changes Since the 1950s, I–O models have been extensively used to compare the structure of production over time and across countries. Pioneer researchers in the field include L (1951), R (1956) and C and W (1958). Interest in the study of structural change re-emerged in the 1980s (R and M, 1989). In Greece, various economists have applied I–O analysis for studies at national and regional levels. For example, S and M (1980) and S (1986) estimated and analysed a time series of I–O tables for 1958–77 and 1960–80, respectively, for the Greek economy, while M (1989) described analytically the construction of the national I–O table for 1980. M and S (1989) used I–O to estimate the contribution of the food sector to economic growth in Greece. Moreover, M and S (1991) suggested a new approach – that of I–O elasticities that incorporate both multiplier effects and the relative size of economic sectors – to identify the important economic sectors of Greece. T and M (1995) explored the dynamics of the economic sectors in the Cretan economy by comparing several impact indicators and identified the regional key sectors. Using a regional I–O model for Crete, the same authors investigated the role of the tourism and agri-food sectors in the development prospects of the Cretan economy (T and M, 1999). In the same framework, they also estimated the effects of Greece’s accession to the European Union on its domestic economy (M and T, 1999). In addition, M et al. (1999) examined the dynamics of the tobacco sector in the regional development of Macedonia and Thrace. Despite the above efforts, it seems there is a lack of literature about changes in the structure of production over time both at the national and regional levels. The only relevant study on this subject is by S (1980), who examined structural changes in the Greek economy between 1958 and 1970. The use of I–O models is a valuable tool for uncovering the important dimensions of structural
change in an economy. The measures employed in this study to investigate structural changes in the regional economy of EMT are described below.4 Input–output multipliers I–O multipliers measure the response of the economy to an exogenous change in final demand. They are conceived as indicators of the importance of particular sectors and measure the interdependence of the sectoral structure. In this paper, three of the most frequently used multipliers are employed.5 First, the output multiplier for a sector j is defined as the total production in all sectors of the economy necessary to satisfy a unit of final demand for sector j’s output (M and B, 1985). It is estimated by summing each column of the total requirements matrix: n
O.j ó ; zij
jó1, 2, . . . , n
(1)
ió1
where O.j is the output multiplier of sector j and zij is the element of total requirements matrix. Next, income and employment multipliers (M and B, 1985) are estimated by dividing the direct and indirect income or employment effect by the corresponding direct effect. Thus, the direct income effect of sector j is defined as: DIEj óHj /xj
(2)
where Hj is the income of sector j and xj is the total output of sector j. The direct and indirect income effect of sector j is defined as: n
DIIEj ó ; zij DIEi
(3)
ió1
The direct employment effect of sector j is defined as: DEEj óEj /xj
(4)
where Ej is the employment of sector j. Finally, the direct and indirect employment effect is defined as: n
DIEEj ó ; zij DEEi
(5)
ió1
Input–output elasticities Although I–O multipliers are the most widely used measures for estimating the economy-wide impacts of changes in final demand, they neglect the relative size of a sector in an economy. Therefore, M and S (1991) have suggested I–O elasticities as indicators for estimating sectoral potentials on the growth of an economy. I–O elasticities reveal the percentage change in total output, income or employment of the economy due to percentage changes in
Structural Changes in Less Developed Areas: An Input–Output Framework the final demand of any sector. Such, elasticities provide better insights than multipliers of the impacts of sectoral changes on the economy. Within the framework of I–O analysis, the output elasticity for sector j is estimated as: n
OEj ó ; zij (yj /X)
jó1, 2, . . . , n
(6)
ió1
where zij is the element of the Leontief inverse,yj is the final demand for the sector j and X is the total regional output.6 The corresponding income elasticity for sector j is computed as:
n
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IEj ó ; (Hi /xj)zij /(Hj /xj)](yj /X)
jó1, 2, . . . , n
ió1
(7)
where Hi /xj is the direct income coefficient. Finally, the employment elasticity of sector j is:
n
EEj ó ; (Ei /xj)zij /(Ej /xj) (yj /X) ió1
jó1, 2, . . . , n (8)
where Ei/xj is the direct employment coefficient. Causative matrix As a final means of fulfilling the objective of this study, the causative matrix approach is used for measuring temporal changes. Applications of the causative matrix approach to the analysis of structural changes at two distinct points of time has been conducted in other contexts, particularly in fields that employ Markov chain analysis. J et al. (1990) presented an extension to I–O analysis of the causative matrix method to evaluate the change between two matrices. This method identifies not only the contributions of economic sectors with respect to the whole economy, but also focuses on the intersectoral interrelationships. Following the I–O notation specified above, there are two possibilities: working on the technical coefficients matrix, A, or the inverse matrix.7 J et al. (1990) choose the second and compute the transition matrix (standardized Leontief inverse), K, by the formula: KóZMñ1
(9)
where Z was defined above and M is the diagonal matrix whose elements Mjj equal the sum of the jth column of Z. The elements of each column of the Leontief inverse are normalized by their respective column sums, as the transition matrices must have column sums equal to 1. This process standardizes for changes in magnitudes of
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output multipliers and focuses the analysis upon the relative influences of each sector on each other sector. Given two time periods, t and tò1, the corresponding transition matrices are assumed to be linked by the formula: Ktò1 óCKt
(10)
where Ktò1 and Kt are calculated according to equation (9), and C is the causative matrix, which is defined as follows: CóKtò1 Kñ1 t
(11)
Matrix C explains the change between the transition matrices Kt and Ktò1 through the interpretation of the elements and row sums of C.8 It is also called left causative matrix.9 Matrix C may contain negative terms, where a negative Cik implies a reduction in sector i’s contribution to sector j’s output multiplier due to the presence of sector k. All column sums of C equal 1. Row sums less than 1 indicate smaller contributions to output multipliers, i.e. the corresponding sectors recording smaller impacts when final demands in other sectors change (and vice versa in the case of row sums greater than 1).10 Negative deviations of the diagonal elements of sectors from 1 imply decreased relative internalization of their own final demand output impacts (and vice versa in the case of positive deviations of the diagonal elements from 1). The causative matrix approach has the advantage of capturing both the direct changes in interactions and the relative changes due to the presence of other sectors.11 Decomposition of structural change Differences in the structure of an economy between two different points in time can be shown on production and employment data. More specifically, the differences in output and employment levels and in the structure of the economy can be depicted with the help of the I–O model basic equation: XóZy
(12)
where all terms are as defined above. If the difference in gross outputs between two different years, t and tò1, are expressed by equation (12), then following S (1989), the two general categories of structural change that determine them can be identified as changes in technical coefficients and changes in final demand. Thus, *Xó(Z tò1 ñZ t)ytò1 òZ t (ytò1 ñyt)
(13)
where X is the difference in total outputs; and Z t and Z tò1, and yt and ytò1 are the inverse matrices and the final demands, respectively, in two different years.12 In the first term on the right-hand side of equation (13), the difference in the inverse matrices of input
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coefficients weighted with the tò1 level of final demand, results in the gross production change between t and tò1 that is attributed exclusively to changing coefficients given period tò1’s final demand. In the second term, the difference of final demand weighted with the inverse input coefficients of the year t results in the gross production change between t and tò1 solely attributable to changes in final demand.
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Data The estimates presented in this paper were derived from the regional I–O tables for EMT corresponding to 1980 and 1997. The 1980 I–O regional tables were computed from the 187-sector Greek table published by M (1989). The basis of the 1997 regional I–O tables was the latest available 1994 I–O table for the Greek economy (N S S G, 1998), which records 59 sectors. Since the data contained therein relate to 1994, this table was updated to 1997 (M et al., 1984). The original tables were aggregated to 17 sectors following the Greek Standard Industrial Classification. The identity of the leading regional sectors was preserved and the relatively unimportant manufacturing sectors were aggregated. For example, food and beverages and tobacco products retained separate sectors reflecting their relative importance, while other manufacturing sectors merged with other industries in view of their insignificant contribution. Taking into consideration that 40% of the working population of the region is engaged in agriculture, it was decided to disaggregate this sector into four subsectors (cereals,
vegetables, fruits, livestock). In the aggregation process, some information is lost. Employment and income data for each sector (as defined in the regional I–O tables) were obtained from the National Statistical Service of Greece (Labor Force Survey Department), the Ministry of Agriculture (Department of Agricultural Statistics) and the National Accounts of Greece (Division of Primary Sector and Industrial Survey Department). Also, output and input structure data for the agricultural subsectors were obtained directly from the Ministry of Agriculture (Department of Agricultural Statistics), while the I–O structure of food and beverages as well as of tobacco products was obtained by information acquired through business surveys.
RESULTS This section gives a quantitative description of the economic structure of the region EMT for 1980–97, focusing on the 17 economic sectors. Results of output multipliers for 1980 and 1997 are shown in the first and second columns, respectively, of Table 2. Sectors that exhibit relatively high output multipliers in 1980 include food and beverages, livestock, construction, tobacco products, and electricity and water. The output multiplier for food and beverages indicates that an increase of 1 million drachmas in the final demand of this sector calls forth an increase of the total regional output by 1.958 million drachmas. For 1997, food and beverages, tobacco products, construction, other industries and vegetables are the sectors with the largest output multipliers. The output multipliers for cereals
Table 2. Sectoral multipliers for 1980 and 1997 Output Sectors Cereals Vegetables Fruits Livestock Forestry Fishing Mining Food and beverages Tobacco products Other industries Electricity and water Construction Trade and hotels Transport and communication Finance Public administration and defence Other services
1980 1.045 1.061 1.038 1.579 1.002 1.247 1.026 1.958 1.352 1.259 1.292 1.391 1.275 1.189 1.133 1.094 1.253
(14) (13) (15) (2) (17) (9) (16) (1) (4) (7) (5) (3) (6) (10) (11) (12) (8)
Income 1997 1.303 1.442 1.399 1.372 1.033 1.304 1.023 1.998 1.598 1.478 1.235 1.586 1.436 1.317 1.219 1.300 1.205
(11) (5) (7) (8) (16) (10) (17) (1) (2) (4) (13) (3) (6) (9) (14) (12) (15)
1980 1.033 1.048 1.012 2.581 1.002 1.144 1.025 3.155 3.380 1.326 1.331 1.322 1.289 1.166 1.236 1.076 1.091
(14) (13) (16) (3) (17) (10) (15) (2) (1) (5) (4) (6) (7) (9) (8) (12) (11)
Employment 1997
1.286 1.277 1.317 1.469 1.536 1.297 1.145 2.856 2.347 2.298 1.196 1.566 1.149 1.375 1.539 1.058 1.115
(11) (12) (9) (7) (6) (10) (15) (1) (2) (3) (13) (4) (14) (8) (5) (17) (16)
1980 1.034 1.049 1.014 2.658 1.003 1.181 1.023 3.324 2.235 1.373 1.324 1.298 1.264 1.163 1.229 1.075 1.083
(14) (13) (16) (2) (17) (9) (15) (1) (3) (4) (5) (6) (7) (10) (8) (12) (11)
1997 1.246 (10) 1.532 (5) 1.272 (9) 1.298 (8) 1.011 (17) 1.207 (12) 1.231 (11) 2.494 (1) 2.210 (2) 1.128 (15) 1.298 (7)) 1.665 (4) 1.195 (13) 1.375 (6) 1.761 (3) 1.073 (16) 1.134 (14)
Notes: 1. Figures are input–output multipliers and indicate the impact of changes in final demand on output, income and employment throughout the economy. 2. Corresponding sectoral rankings are in parentheses.
Structural Changes in Less Developed Areas: An Input–Output Framework
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Table 3. Sectoral elasticities for 1980 and 1997 Output Sectors
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Cereals Vegetables Fruits Livestock Forestry Fishing Mining Food and beverages Tobacco products Other industries Electricity and water Construction Trade and hotels Transport and communication Finance Public administration and defence Other services
1980 0.0842 0.0075 0.0089 0.0994 0.0105 0.0066 0.0109 0.1313 0.0381 0.1359 0.0045 0.1774 0.1255 0.0402 0.0274 0.0629 0.0287
(6) (15) (14) (5) (13) (16) (12) (3) (9) (2) (17) (1) (4) (8) (11) (7) (10)
Income 1997 0.0141 0.0006 0.0003 0.0020 0.0011 0.0022 0.0712 0.1573 0.0039 0.4347 0.0005 0.1172 0.0241 0.0344 0.0690 0.0172 0.0627
(10) (15) (17) (13) (14) (12) (4) (2) (11) (1) (16) (3) (8) (7) (5) (9) (6)
1980 0.0832 0.0078 0.0094 0.1928 0.0107 0.0144 0.0125 0.5753 0.6068 0.1341 0.0151 0.1624 0.1141 0.0408 0.0364 0.0647 0.0271
(7) (17) (16) (3) (15) (13) (14) (2) (1) (5) (12) (4) (6) (9) (10) (8) (11)
Employment 1997
0.0150 0.0003 0.0003 0.0032 0.0434 0.7177 0.0821 0.2122 0.0074 0.4047 0.0005 0.1587 0.0199 0.0476 0.0843 0.0181 0.0603
(12) (16) (17) (14) (9) (1) (6) (3) (13) (2) (15) (4) (10) (8) (5) (11) (7)
1980 0.0832 0.0079 0.0096 0.2003 0.0107 0.0166 0.0124 0.6762 0.5916 0.1369 0.0147 0.1588 0.1126 0.0406 0.0358 0.0645 0.0269
(7) (17) (16) (3) (15) (12) (14) (1) (2) (5) (13) (4) (6) (9) (10) (8) (11)
1997 0.0136 0.0005 0.0007 0.0020 0.0018 0.0145 0.0864 0.4507 0.0273 0.4228 0.0009 0.1517 0.0198 0.0450 0.0926 0.0181 0.0603
(12) (17) (16) (13) (14) (11) (5) (1) (8) (2) (15) (3) (9) (7) (4) (10) (6)
Notes: 1. Figures are input–output elasticities and reveal the percentage change in total output, income or employment of the economy due to percentage changes in final demand of any sector. 2. Corresponding sectoral rankings are in parentheses.
increased from 1.045 in 1980 to 1.303 in 1997, for vegetables from 1.061 in 1980 to 1.442, and for fruits from 1.038 to 1.399 over the same period. The livestock sector reduced its relative influence on the economy, recording a multiplier of 1.372 in 1997 compared with 1.579 in 1980. A general increase of the size of output multipliers is also recorded for manufacturing sectors. The service sectors have a similar tendency, with the exception of other services, which recorded a decrease on their relative impact on the economy. The third and the forth columns of Table 2 show the sectoral income multipliers for 1980 and 1997, respectively. For 1980, sectors with the highest income multipliers include tobacco products, food and beverages, livestock, electricity and water, and other industries, while for 1997 sectors with comparatively high income multipliers include food and beverages, tobacco products, other industries, construction, and finance. The reason behind high-income multipliers in the sectors of food and beverages and tobacco products is not only their low direct income coefficients, but also their significant intersectoral linkages. With the exception of livestock, agricultural sectors again recorded an increase of income multipliers during 1980–97. In Table 2, the fifth and sixth columns show the employment multipliers. Food and beverages and tobacco products are again the sectors with relatively high values. The high indirect output requirements by these sectors, combined with their low labour-output ratios, contribute to these high employment multipliers. As regards the agricultural sectors, estimated multipliers are relatively low, mostly due to the high direct employment linkages of these sectors rather than to the indirect employment effects, which are rather low.
Food and beverages and tobacco products industries are ranked at the top of all considered sectors in terms of output, income and employment multipliers. Nonetheless, the I–O multipliers of other regional sectors increase or decrease over the period mentioned above, thus implying an expansion or contraction of a particular sector’s economic activity as a result of structural change in intersectoral relationships. Further, the output, income and employment elasticities computed for the 17 sectors of the regional economy are reported in Table 3. For 1980, the construction sector seems to have the highest potential to generate output in the regional economy. A 10% increase in the final demand of this sector leads to a 1.774% increase in the output of the regional economy. In addition, the livestock and cereals sectors have a high output potential. Other sectors with large output elasticities include other industries, food and beverages, and trade and hotels. Sectors ranked high based on output elasticities are also ranked high based on income and employment elasticities, respectively. Although the ranking changes slightly, all sectors ranked in the top five based on output elasticities follow the same pattern in the case of income and employment generation (except for trade and hotels). For 1997, rankings based on output elasticities identify other industries, food and beverages, construction, mining, and finance as the top five sectors for output generation. As for income and employment potentials, these rankings recorded a rather small difference. During the period under study, the agricultural sectors became less relevant for the regional economy in terms of generating output, income and employment exhibiting reduced level of elasticities. On the other
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hand, as an evidence of the structural changes that have occurred in the regional economy, the remaining sectors of the local economy increased or decreased their relative importance with regard to their potential to generate output, income or employment. To determine whether there is any pattern in the size of multipliers and elasticities, correlation coefficients representing relationships among the various indicators were estimated. These coefficients were computed using sectoral rankings based on those indicators. Results suggest that the correlation among the regional indices during 1980–97 is relatively weak or moderate. Hence, a weak correlation exists between income elasticity and output, income and employment multipliers (coefficients of 0.194, 0.172, and 0.243, respectively) and between income elasticities (0.238). Also, output elasticities demonstrate a fairly low correlation with output and employment multipliers (coefficients of 0.294 and 0.069, respectively). A moderate correlation is also observed between output multipliers (0.618), income multipliers (0.515), output elasticities (0.689) and employment elasticities (0.588). In addition, income multipliers are moderately correlated with output and employment multipliers (coefficients of 0.596 and 0.525, respectively) as well as with income and output elasticities (0.500). The weak and moderate correlation among the rank measurements based on multipliers and elasticities indicates that significant differences exist between the estimates used to assess the importance of sectors as stimulators of output, income and employment changes in the economy of the region during 1980–97. Table 4 presents the results of the left causative matrix for each of the 17 sectors, both for 1997 compared with 1980 and for 1980 compared with 1997, based on the deviations of their dominant diagonal elements and sums of their respective row elements from unity.13 Briefly, results for 1997 compared with 1980 show that the row sums exceed unity for cereals, vegetables, forestry, fishing, tobacco products, construction, trade and hotels, transport and communication, finance and public administration, and defence, implying their increasing role as suppliers. The absolute change in the total output multipliers of the specified sectors (Table 2) reveals that final demand in these sectors generates strengthened total output impacts. At the same time, the row sums of the causative matrix elements corresponding to these sectors, suggest that final demand in other sectors is overall generating increased output impacts. Referring to cereals and vegetables, their diagonal elements exceed unity. Hence, their final demand impacts, relative to that of other sectors, are increasingly internalized within the sectors. Fruits and livestock recorded an opposite situation: relative to the impacts on other sectors, the final demand of these sectors creates a reduced output impact on their own sectors. The results for 1980 compared with 1997 indicate that the row sums exceed unity for
Table 4. Sectoral structural changes for 1980–97 based on left causative matrix results 1997 compared with 1980
Sectors Cereals Vegetables Fruits Livestock Forestry Fishing Mining Food and beverages Tobacco products Other industries Electricity and water Construction Trade and hotels Transport and communication Finance Public administration and defence Other services
1980 compared with 1997
Diagonal elements
Row sums
Diagonal elements
Row sums
1.0390 1.1455 1.0901 0.7061 1.0304 1.0947 0.9963
1.1788 1.1021 0.9131 0.8042 1.0256 1.0903 0.9518
0.9625 0.8740 0.9194 1.4154 0.9704 0.9134 1.0038
0.8010 0.9132 1.0885 1.2347 0.9716 0.9164 1.0588
0.9951 1.0846 1.0530
0.8844 1.0846 0.7828
1.0106 0.9220 0.9513
1.1009 0.9220 1.7830
1.0010 1.1397 1.1100
0.8746 1.1609 1.0812
1.0001 0.8778 0.8997
1.0266 0.8598 0.7856
1.0019 1.0541
1.0999 1.0022
0.8550 0.9485
0.7751 0.8764
1.1882 0.9659
1.0610 0.9026
0.8416 1.0343
0.7974 1.0891
fruits, livestock, mining, food and beverages, other industries, electricity and water, and other services. Thus, these sectors are more competitive in supplying the requirements of sectors. This implies they have a greater contribution to output multipliers than do other sectors. Finally, other sectors recorded row sums less than unity, indicating that they have become less important suppliers to sectors of the regional economy. Table 5 shows the sources of changes in output and employment between 1980 and 1997. The second column presents the percentage change in sectoral gross output, solely attributed to changes in technical coefficients. In more than half of the regional production sectors, changing coefficients result in increases in their output requirements. The largest positive impact (over 20%) of changing technical relationships on gross output requirements is observed in livestock, mining, electricity and water, and finance. The largest reductions (over 20%) in output requirements because of technological change is recorded in cereals, fruits and other industries. The third column shows the percentage change in gross production that is exclusively due to changes in final demand. The largest percentage increase occurs in transport and communications and the lowest one in tobacco products. Comparing the percentage changes due to final demand with those attributed to changes in technical coefficients (ignoring the signs), it is observed that in all sectors the impact of final demand on gross production was larger than that of changing coefficients.
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Table 5. Decomposition of forces determining output and employment change between 1980 and 1997
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Sectors
Per cent change in gross output
Per cent change in employment
Due to technical coefficients change
Due to technical coefficients change
Due to employment coefficients change
38.86 ñ47.60 ñ27.80 ñ90.15 8.79 34.61 ñ45.76 15.76 8.85 ñ9.47 64.16 ñ12.43 30.30 69.74 39.69 20.77 75.90
ñ157.39 ñ89.41 ñ56.08 ñ65.01 ñ65.46 ñ126.52 ñ55.55 53.55 31.49 56.67 ñ81.56 89.85 ñ136.34 ñ77.07 40.31 ñ66.58 ñ77.31
Total
Cereals Vegetables Fruits Livestock Forestry Fishing Mining Food and beverages Tobacco products Other industries Electricity and water Construction Trade and hotels Transport and communication Finance Public administration and defence Other services
56.20 117.34 74.86 152.74 102.53 84.99 155.93 94.97 81.40 46.80 172.95 123.44 128.42 197.74 207.17 133.78 155.16
ñ39.01 12.46 ñ44.09 20.08 16.83 ñ7.24 66.32 ñ2.24 10.36 ñ25.17 82.92 ñ11.46 ñ9.10 ñ16.66 74.29 6.46 8.69
The fifth column of Table 5 presents the changes in employment that are solely due to changes in the technical coefficients. Note that in more than half of the regional sectors, changes in technical coefficients resulted in an increase of labour requirements. In the case of cereals, fishing, electricity and water, trade and hotels, transport and communication, finance, public administration, defence, and other services, increases in labour requirements exceeded 20%, while for the remaining sectors that recorded increases in labour requirements, the changes were less than 20%. The rest of the sectors recorded a reduction in labour requirements, which is exclusively attributed to changes in technical coefficients. The changes in employment coefficients, shown in the sixth column, resulted in considerable labour savings, with the exception of food and beverages, tobacco products, other industries, and construction and finance. Generally, the effect of the changed employment coefficients (ignoring the signs) on labour requirements was, with the exception of the livestock sector, higher than the effect of technical change. CONCLUSIONS This paper has analysed and quantified the changes in the economic structure of the EMT region, a primarily agricultural area in Greece, which (similar to other parts of the country) has faced serious structural problems since the accession of Greece into the EU. Sectoral multipliers were used as quantitative measures of dynamics in the regional economy between
Due to final demand change 95.21 104.88 118.95 132.66 85.70 92.23 89.61 97.21 71.04 71.97 90.03 134.90 137.52 214.40 132.88 127.32 146.47
Total ñ118.53 ñ137.01 ñ83.88 ñ155.16 ñ56.67 ñ91.91 ñ101.31 69.31 40.34 47.20 ñ17.40 77.42 ñ106.04 ñ7.33 80.00 ñ45.81 ñ1.41
1980 and 1997. In addition, the use of I–O elasticities distinguished important economic sectors according to their relative size. Moreover, the use of a causative matrix approach provided information on the structural changes in the web of I–O relationships over time, while the structural decomposition distinguished between technical and final demand change in the regional economy. Estimated I–O sectoral multipliers strongly support the contention that both food and beverages and tobacco products form an important part of the local economy in terms of output, income and employment. The examination of changes in the regional economy during 1980 and 1997 based on elasticities revealed a shift of the local economic activity from agricultural sectors towards manufacturing sectors and services. This is an indication that their relative size, in terms of total sales to final demand, decreases according to their contribution to a region’s growth potential. The weak and moderate correlation among the most of the ranked measurements used to assess output, income and employment potentials is an indication that the economic structure of production of the region has recorded significant dissimilarities during the period under study. The estimated causative matrices revealed that during 1980–97 most of the sectors are characterized by a greater endogenization of their own final demand impacts and increased output impacts caused from other sectors. The structural decomposition analysis showed that the effects of final demand on gross production were more important than those that occurred due to changes in the regional technical
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coefficients. Regarding the employment requirements, it was found that significant labour saving occurred as a result of combined effect of technical changes and changes in employment coefficients, with the last factor being the dominant one. The results suggest that all of the regional sectors have experienced rather major structural changes during the period under study. In addition, findings indicate that the economy of EMT is still dependent on agricultural activities, which are also strongly linked with the rest of the regional economy. Thus, it is evident that the EU Common Agricultural Policy reforms of the late 1980s and early 1990s have increased the need for modernization and better management in the agricultural sector of the region, but so far these changes seem to occur rather slowly. However, the forthcoming reform of the Common Agricultural Policy that will also take into account EU enlargement and the expected competition from the new EU Member States (especially in the case of cereals, vegetables and fruits) clearly point to the need for necessary actions for the much needed improvement in agricultural productivity and competitiveness that will eventually create growth and employment in the region, and generally contribute to the policy target of economic cohesion of EMT with the rest of the EU. On the other hand, the analysis of structural changes revealed that the manufacturing and service sectors have increased in importance in the regional economy. These sectors are expected to play a significant role in regional economic development in the future. Hence, the formulation of a realistic developing plan to sustain economic growth in the region can be achieved by combining the expansion of sectors with high I–O multipliers and elasticities. Acknowledgements – The authors gratefully acknowledge the helpful comments and suggestions of the Editors and two anonymous referees.
4.
5.
6.
7.
8.
NOTES 1. Influential work by B and S-I-M (1992, 1995) and S-I-M (1996a, b) on the convergence properties of regions within various countries (including regions within several European countries) has shown that poorer regions within a country tend to grow faster than richer regions. The speed of convergence, however, is not rapid (about 2% per year). 2. For more detailed exposure on this technique, see J and L (1987), T and M (1995) and L et al. (2000). 3. The GRIT technique, as originally developed by J et al. (1979), used the Simple Location Quotient as a method of coefficient reduction. The quotient itself compares the relative importance of a sector regionally to its relative importance in the nation. A potential drawback of the quotient approach is that only the size of the selling sector is taken into account, although
9.
10.
11.
clearly the relative size of the purchasing sector may also be of crucial importance in determining the extent of regional imports. The use of the Cross Industrial Location Quotient, proposed by J and L (1987), helps to overcome this problem by taking into account the relative local importance of the purchasing sector as well as of the selling sector. Thus, it compares the proportion of regional employment in selling sector i in the nation to that of purchasing sector j. The following notation is used throughout: Aó{aij}óxij/xj is the direct requirements coefficient matrix, which is also called the technical coefficients matrix, where xij is sector j’s direct input from sector i, and xj is the total output of sector j; X is the gross output; y is the final demand; and Zó{zij}ó(IñA)ñ1 is the total requirements matrix, which is often referred to as the Leontief inverse matrix. These satisfy the usual I–O equation: Xó(IñA)ñ1y. For additional details on I–O multipliers, see M (1965), R (1972) and P and H (1982). Gross output is defined as Xó&nió1 xi, where xi ó&njó1 zij yj is the output of sector i and zij is the element of the Leontief inverse, while yj is the final demand for sector j. The change in the total output of sector i due to a unit change in the final demand of sector j is dxi/dyjózij. Summing over all sectors yields &nió1 (dxi/dyj )ó&nió1 zij ób.j, where b.j is known as backward linkage used to assess output potentials of economic sectors (A and H, 1971; H and S, 1985). However, the index b.j can mislead policy-makers about the importance of a sector because it does not take into account the relative size of that sector. Since elasticities take into account the relative sizes of economic sectors, they provide a more reliable identification of key sectors in an economy. J et al. (1990) focus upon changes in the Leontief inverse matrix to understand changes in input intensities and output multipliers. The diagonally dominant Leontief inverse facilitates the interpretation of the causative matrix elements. A reverse comparison is possible, tò1 on t, instead ˜ Ktò1, where C ˜ is the causative matrix of t on tò1. KtóC for the reverse analysis, is denoted as follows: ñ1 ˜ óKt Kñ1 C tò1 óC . J et al. (1990) suggested a right causative matrix, R, defined for sales coefficients and forward linkages: Ktò1 óRKt, RóKñ1 t Ktò1. The left causative matrix defined for sales coefficients makes less sense because it focuses on the inflow perspective, where sectors compete with each other to supply a given sector. Therefore, it is appropriate for the study of changes in backward linkages. The causative matrix can be defined as follows: ñ1 CóZtò1 Mñ1 tò1 Mt Z t . It is therefore related to the ratio of output multipliers (Mñ1 tò1 Mt). If the output multipliers do not change, this term will be identity. C then depends entirely on the difference between Kt and Ktñ1. J et al. (1990) have proposed the double causative model where both effects described in the right and left matrices are explicit in the same model. However, as they noted: ‘The use of a doubly causative model
Structural Changes in Less Developed Areas: An Input–Output Framework would require both additional data and additional consideration of appropriate techniques’. An alternative was proposed by D M (2000): the bicausative model. De Mesnard proved that the model is deceptive because the diagonal matrices are unidentified and the interpretation of results is unclear. 12. For decomposition of forces determining employment,
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in equation (13) the inverse matrices and final demands are replaced by I–O matrices and employment coefficients, respectively, in two different years (S, 1980). 13. The two computations are conducted to provide a more consistent check of sorts. That is, if the results are asymmetric in interpretation, that would throw doubt upon the credibility of the approach.
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REFERENCES A N. and H N. (1971) Linkages and imports: a comparative study of India and Pakistan, Journal of Developmental Studies 8, 317–323. A K. (1990) The region of East Macedonia and Thrace, in The Development of Greece: Past, Present and Political Proposals, pp. 362–365. Center of Planning and Economic Research, Athens. B R. J. and S-I-M X. (1992) Convergence, Journal of Political Economy 100, 223–251. B R. J. and S-I-M X. (1995) Economic Growth. McGraw-Hill, New York. B D. (1998) The Situation of Agriculture, Food and the Rural Economy of Greece, 1997. Ministry of Agriculture, Athens. C H. B. (1980) Interactions between industrialization and exports, American Economic Review 70, 281–287. C H. B. and W T. (1958) International comparisons of the structure of production, Econometrica 26, 487–521. C S. and M E. E. (1969) Applicability and limitations in the use of national input–output tables for regional studies, Papers in Regional Science 23, 65–77. D M L. (2000) Bicausative matrices to measure structural change: are they a good tool?, Annals of Regional Science 34, 421–449. D J. (1974) The analysis of structural constraints in developing economies: a case study, Oxford Bulletin of Economics and Statistics 36, 95–108. E (various issues) The Greek Economy. All Media Publ., Athens. E C (1999) Sixth Periodic Report on the Social and Economic Situation and Development of the Regions in the European Union. European Commission, Directorate General for Regional Policy and Cohesion, Brussels. G D., L P. and M G. (1997) Regional inequalities in Greece, 1961–1991, Topos 13, 47–61. H M. and S G. (1985) Measuring backward and forward linkages in the US food and fiber system, Agricultural Economics Research 37, 33–39. I Y. M. and P G. (2000) Regional Disparities in Greece and the Performance of Crete, Peloponnese and Thessaly. Discussion Paper 2000-08. Department of Economics, European Investment Bank, Tufts University. J R. W., R P. and P D. (1990) A causative matrix approach to interpreting structural change, Economic Systems Research 2, 259–269. J R. C., M T. D. and K N. D. (1979) Regional Economic Planning: Generation of Regional Input– Output Analysis. Croom Helm, London. J P. M. and L P. M. K. (1987) The application of modified GRIT input–output procedures to rural development analysis in Grampian region, Journal of Agricultural Economics 32, 243–256. K N., M S. and P A. (1999) Analysis of Regional Productive System. RITTS Eastern Macedonia and Thrace, Thessaloniki. K N. and S E. (1998) Neo-industrialisation and peripherality evidence from regions of Northern Greece, Geoforum 29, 37–49. L W. (1951) The Structure of the American Economy, 1919–1939. Oxford University Press, New York. L E., M K., T V., F C. and G, K. (2000) Regional economic development and environmental repercussions: an environmental input–output approach, International Advances in Economic Research 6, 373–386. M K., F C., T V., L S. and P K. (1999) The dynamics of crop sectors in regional development: the case of tobacco, International Advances in Economic Research 5, 255–268. M K., P A. and D A. L. (1984) Building Input–Output Models Using Non-Survey Techniques. Southern Rural Development Center, Kentucky. M K. and S C. M. (1989) The food sector and economic growth, Food Policy 14, 67–72. M K. and S C. M. (1991) A new approach to determine sectoral priorities in an economy: input–output elasticities, Applied Economics 23, 247–254. M K. and T V. (1999) The impact of EU membership: lesson from the Greek experience, Economia Internazionale 52, 173–189. M L., P A. P. and P G. T. (1996) European Integration and Regional Convergence in Greece. Discussion Paper. University of Economics and Business, Athens. M W. H. (1965) The Elements of Input–Output Analysis. Random House, New York. M R. E. and B P. D. (1985) Input–Output Analysis: Foundations and Extensions. Prentice-Hall, Englewood Cliffs. M N. A. (1989) Analytical Input–Output Tables of the Greek Economy – Year 1980. Center of Planning and Economic Research, Athens.
Downloaded By: [University of Patras] At: 15:23 19 October 2010
614
Claudia Ciobanu et al.
N S S G (1998) National Accounts of Greece 1988–1997. National Statistical Service of Greece, Athens. P G. and S G. (2000) Regional inequality in Greece, Papers in Regional Science 79, 57–74. P P. J. and H A. J. (1982) Estimating input–output multipliers – a new hybrid approach, Environment and Planning A14, 335–342. P D. (1995) Input–output analysis of Scottish forestry strategies. Unpublished PhD thesis, University of Aberdeen. P D. and T K. J. (1993) Input–output evaluation of rural development: a forestry-centered application, Journal of Rural Studies 9, 351–358. R P. N. (1956) Studies in Intersectoral Relations. North-Holland, Amsterdam. R H. W. (1972) Input–Output and Regional Economics. Halsted, New York. R A. and C S. (1996) Input–output structural decomposition analysis: a critical appraisal, Economic Systems Research 8, 33–62. R A. and C C. Y. (1991) Sources of change in energy use in the US economy, 1972–1982: a structural decomposition analysis, Resources and Energy 13, 1–21. R A. and M W. (1989) Input–output analysis: the first fifty years, Economic Systems Research 1, 229–271. R J. I. (1983) Nonsurvey techniques: a critical review of the theory and the evidence, International Regional Science Review 8, 189–212. S-I-M X. (1996a) Regional cohesion: evidence and theories of regional growth and convergence, European Economic Review 40, 1325–1352. S-I-M X. (1996b) The classical approach to convergence analysis, Economic Journal 106, 1019–1036. S J. (1989) Input–output structural decomposition analysis for Austria, Journal of Policy Modeling 2, 45–66. S, T. (1980) Structural Changes in the Economy: Intertemporal Analysis in Input–Output Framework. Center of Planning and Economic Research, Athens. S T. (1986) Input–Output Tables of the Greek Economy 1960–1980. Center of Planning and Economic Research, Athens. S T. and M G. (1980) Input–Output Tables of the Greek Economy 1958–1977. Center of Planning and Economic Research, Athens. T V. and M K. (1999) Tourism and agri-food as a growth stimulus to a rural economy: the Mediterranean island of Crete, Journal of Applied Input–Output Analysis 5, 69–81. T V. M. and M K. (1995) Revealing a region’s growth potential through the internal structure of the economy, International Advances in Economic Research 1, 304–313.
