ISAE 7giu05def

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Published on October 31, 2007

Author: Talya

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INSIDE THE BLACKBOX: ECONOMIC PERFORMANCE AND TECHNOLOGY ADOPTION WHEN SPACE AND PRODUCT RELATIONSHIPS MATTER:  INSIDE THE BLACKBOX: ECONOMIC PERFORMANCE AND TECHNOLOGY ADOPTION WHEN SPACE AND PRODUCT RELATIONSHIPS MATTER Leonardo Becchetti University of Rome Tor Vergata Monitoring Italy 2005 Productivity, Growth & Competitiveness Rome, ISAE, June 7th 2005 Annalisa Castelli University of Rome Tor Vergata MOTIVATION & RESULTS:  MOTIVATION & RESULTS We highlight the relevance of studying the performance of productive units by considering space and product relationships. By applying the district/no district and independent/subcontractee status taxonomy, we find that district independent firms have higher value added and are more efficient than non district independent firms, but that ICT investment improve efficiency only for the latter. Our findings suggest that: i) the quality of space relationships (district location) positively affects unmeasured forms of human and social capital; ii) ICT adoption has a stronger impact on non district independent firms as the improvement of electronic links is more beneficial for productive units with poorer space relationships. BACKGROUND LITERATURE (1):  BACKGROUND LITERATURE (1) Limits of the ISTAT classification: 1) Dichotomous indicators fail to take into account the intrinsic heterogeneity of industrial districts account (Tattara, 2002 and Iuzzolino, 2004) 2) Focus on employment density in small and medium sized enterprises, which leads to neglecting the contribution of large firms and urbanization on local corporate performance (Iuzzolino, 2004). 3) Econometric estimates limiting the analysis to the effect of an ISTAT(-like) ID variable neglect the importance of the position of the productive units along the value chain. BACKGROUND LITERATURE (2):  BACKGROUND LITERATURE (2) Alternative solutions: the relative density of manufacturing employment with respect to national average in the local labour system or in the municipality; a global specialization index (Glaeser et al., 1992; Henderson, 1997; Henderson et al., 1995; Costa et al., 1999) calculated on employees and on productive units in the local labour system or in the municipality; industry specific specialization indexes (Glaeser et al., 1992; Bronzini, 2003; Becchetti et al., 2005) combination of ISTAT ID with value chain position indicators (this paper) SPACE AND PRODUCT RELATIONSHIPS:  SPACE AND PRODUCT RELATIONSHIPS Space district classification We use the “industrial district” concept as a proxi for space relationships. Firms belonging to districts have been identified using the ISTAT quantitative indicator. Product position in the value chain Product relationships have been proxied using qualitative information on firms’ subcontracting activity. Firms having more (less) than 70% of their net sales subcontracted have been classified as subcontractee (independent). Matching the two we get our fundamental taxonomy district/no district - independent/subcontractee DATA:  DATA Data come from the last two waves (1995-97 and 1998-2000) of the Mediocredito Centrale Survey. We focus on a sample of 3903 firms selected from the 1998-2000 wave. In order to test if ICT investment carried out in the previous period has positive and significant impact on productive efficiency in the following period we match the last wave with the 1995-97 one and obtain a sample of 1221 firms. We then classify the obtained samples by our proposed taxonomy based on geographical agglomeration and position in the value chain. METHODOLOGY:  METHODOLOGY Descriptive evidence highlights differences among the 4 subgroups of firms. In order to disentangle the various determinants of these differences we follow 3 steps: OLS: we test the impact of traditional controls such as age, size etc. on a performance measure. Stochastic Frontier Approach: we estimate a stochastic frontier production function to test whether the proposed taxonomy affects productive efficiency. Difference in distance estimate: we follow this two step procedure to test the effect of ICT investment on productive efficiency. 1. OLS:  1. OLS The highlighted heterogeneity among subgroups could depend on 2 classes of determinants (age, size, monopoly rents etc. or space and product relationships). The problem is that the two classes of variables are strictly correlated. To disentangle the two effects we regress value added per worker on age, size and other traditional controls in order to test whether the role of space and product relationship is significant. We find that district firms have significantly higher value added net of considered controls. Repeating the estimate on subgroups of independent and subcontractee firms we find that all the effect is due to the significantly higher value added of district with respect to non district independent firms. 2. STOCHASTIC FRONTIER APPROACH (a):  2. STOCHASTIC FRONTIER APPROACH (a) OLS estimates do not discriminate between rent extraction and productive efficiency and do not simultaneously take into account distances from the efficiency frontier for a given production function. The SFA allows to distinguish between production inputs and efficiency/inefficiency factors and to disentangle distances from the efficient frontier between those due to systematic components and those due to noise. We estimate the model with Frontier 4.1 on both a three year panel than a cross-section in which all quantitative variables are included as three year averages in order to smooth potential, year specific, measurement inaccuracies. 2. STOCHASTIC FRONTIER APPROACH (b):  2. STOCHASTIC FRONTIER APPROACH (b) The estimated model: (1) (2) space relationships significantly and positively affect productive efficiency since district firms, whatever their position in the value chain, are significantly less distant from the efficient frontier. 3. DIFFERENCE IN DISTANCE (a):  3. DIFFERENCE IN DISTANCE (a) The evaluation of whether ICT investment in the previous wave (1995-97) has positive and significant effects on productive efficicency in the following wave (1998-00) requires 2 steps: 1st step: we estimate a common stochastic frontier model (the 2 equations above presented, the 2nd including only industry dummies). 2nd step: we regress changes in the estimated distance from the efficient frontier in the two periods on a series of regressors traditionally used in the second equation of the stochastic frontier model. 3. DIFFERENCE IN DISTANCE (b):  3. DIFFERENCE IN DISTANCE (b) among the 4 subgroups of ICT investing firms, only non district independent firms exhibit a significant reduction in distance from the efficient frontier. The chosen specification is the following: SFA RESULTS :  SFA RESULTS A likely interpretation of this result is that space relationships may help to accumulate hidden and unmeasured social and human capital components which significantly affect the productivity of visible and measurable labour and capital inputs. The result is a significantly higher productive efficiency of the two observable inputs. “space relationships significantly and positively affect productive efficiency since district firms, whatever their position in the value chain” DIFFERENCE IN DISTANCE RESULTS:  DIFFERENCE IN DISTANCE RESULTS This result is consistent with the effects of geographical agglomeration. According to the literature, district location fosters hidden or not entirely measurable forms of (human and social) capital by reinforcing informal networks and technological spillovers. The underestimation of the stock of overall capital explains the observed difference in mean and variability of productive efficiency between the district/non district subgroups. By considering that electronic links are a substitute of space in fostering networks, we are not surprised that ICT adoption has a stronger and significant impact on non district independent firms and that ICT is more beneficial for those firms with poorer space relationship. “among the 4 subgroups of ICT investing firms, only non district independent firms exhibit a significant reduction in distance from the efficient frontier” CONCLUSIONS:  CONCLUSIONS Measuring firm intangible assets is becoming of increasing relevance in a framework of global integration in which innovation plays a decisive competitive role. In this paper we have argued that an important dimension of these intangible assets may be incorporated by space and product relationship of individual productive units. Our findings show that quality of space relationships affects firm productivity in both value added per worker and firm efficiency and that ICT adoption generates significant improvement in efficiency only for the subgroup of non district independent firms. We interpret our results by arguing that district location significantly stimulates accumulation of hidden and unmeasured forms of (human and social) capital and that ICT acts as a partial substitute for these factors in firms which do not benefit of local agglomeration economies. FURTHER SUPPORT FOR THE ROBUSTNESS OF THE DISTRICT EFFECT ...(1):  FURTHER SUPPORT FOR THE ROBUSTNESS OF THE DISTRICT EFFECT ...(1) FURTHER SUPPORT FOR THE ROBUSTNESS OF THE DISTRICT EFFECT ...(2):  FURTHER SUPPORT FOR THE ROBUSTNESS OF THE DISTRICT EFFECT ...(2)

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