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Small Business Economics

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01.02.2013

Vertical integration and efficiency: an application to the Italian machine tool industry

verfasst von: Fabio Pieri, Enrico Zaninotto

Erschienen in: Small Business Economics | Ausgabe 2/2013

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Abstract

This paper analyzes the relationship between firm efficiency and vertical integration in the Italian machine tool (MT) industry. The link may really be the result of a two-way causality: the effect may run from productive efficiency to the type of vertical organization (i.e. vertical integration or outsourcing), as a self-selection mechanism, or an effect from the organizational mode to the firm’s performance may (also) be at work. This relationship is empirically investigated in a novel panel dataset comprising about 500 Italian MT builders, implementing two equations and instrumental variables for the two directions of causality. The evidence clearly indicates the self-selection mechanism of the most efficient firms in vertically integrated structures, while an effect from the organizational mode to the firm’s efficiency is not supported.

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Evidence on changes in the vertical organization of production has been recently provided by Malerba et al. (2008) in the computer and semiconductor industries.

Girma and Görg (2004) investigate the effects of outsourcing on productivity and the determinants of outsourcing, but the authors do not include productivity among its determinants. Federico (2010) finds direct support for the self-selection hypothesis (from efficiency to the vertical organization mode), and no support for the other direction, but he clarifies that the data prevent him from performing stronger tests on the effects from the organizational mode to firms’ efficiency.

Comparative results suggest that estimates of inefficiency are robust to the assumed distribution, thus leaving the choice of the distribution more a matter of computational tractability than anything else (see Greene 2008, p. 180).

This issue is much like the heterogeneity (omitted variable) bias problem in standard panel data models.

In the case of a SFM, in which the composed error term is asymmetrically distributed, the heterogeneity bias may still exist, but only minimally, as the correlation between firms’ effects and the explanatory variables is now taken into account in the model (Abdulai and Tietje 2007, p. 7).

We cross-refer the reader to Sect. 6.1 for further details in the interpretation of the inefficiency scores from the TRE model with the Mundlak adjustment (TREMU).

Greene (2005) (MSL), showed that the unconditional likelihood function of the model possesses no closed-form solution, so that employing the MSL estimation, by integrating out ω_i by Monte Carlo methods, may be a solution.

See Wang and Schmidt (2002) for a detailed Monte Carlo comparison between the one-step and two-step procedures in estimating effects of third variables on inefficiency.

Deflators for output and intermediate inputs were built using the value of production series at 2-digit level (Ateco 2007 classification), while, given the unavailability of the investments series at the 2-digit level, the deflator for capital is common to all firms belonging to the aggregate C-D-E Ateco 2007 sectors. Deflators were built as the ratio of the monetary value at current prices, in a given year, over the corresponding value in the chained series, and the base year is 2000.

For example, if differences in output prices mainly depend on the firm-level mark-up and if this may be considered as invariant, a model with firms’ effects would control for the specific price.

Mairesse and Jaumandreau (2005), encouragingly, also found that estimating the revenue function (using nominal output measures) or the proper production function (using real or quantity measures) makes very little difference in terms of estimated output elasticities; as the main concern of our analysis is correct estimation of inefficiency scores via overall residuals, this evidence may further reassure us about the scores obtained.

A value of 1 means that the firm depends on external suppliers for almost all its production inputs; values near 0 indicate that the firm bases its production on its own capital and labor, i.e., it is vertically integrated.

The empirical literature on vertical integration suggests alternative measures compared with the Adelman index (Vannoni 1996). Input–output (I–O) tables were used by Davies and Morris (1995) to build a vertical integration index (VI^k) which aims at capturing intra-firm flows of goods, the ‘heart’ of the vertical integration concept, but it imputes them from intra-industry flows. Our measure of vertical disintegration does not impose common-to-the-industry intra-firm flows, nor do we have the breakdown of turnover by sector, which is a fundamental requirement in order to build the VI^k index.

In fact, the yearly quotas of depreciations and amortizations are computed by following fiscal deductibility purposes, using the coefficients established by the Ministry of Economy and Finance at sectoral level—i.e., they are common to all firms belonging to the same sector—in the Ministerial Decree 31.12.1988.

The inclusion of a measure of size also allows us to control partially for other firms’ characteristics which are not directly observable in our dataset, such as the R&D intensity and the internationalization status, which may well be correlated with both vertical integration and firms’ efficiency.

The idea behind the use of this proxy is that the more assets are specific to the set of activities conducted by the firm, the higher are costs are attached in the case of bankruptcy, due to the lower redeployability. In this sense, it would be more costly to finance these kinds of assets (e.g., R&D investments) with debt. Thus, the debt-to-asset ratio should be negatively related to the amount of firm-specific assets.

All estimations and calculations are based on Stata 10.1 and NLOGIT 4.0 environments.

We cross-refer the reader to Sect. 6.1, for a detailed comparison of TREMU with alternative SFM.

Natural candidates may be fixed management quality, type of machine produced, specific differences in upstream/downstream markets.

As \(\widehat{u}^{\rm TREMU}_{it}\) and UNCE_it result from the estimation of econometric models, potential measurement errors stemming from the corresponding regressions may lead to inefficient estimates: for this reason, we re-estimated A1 using the Prais–Winsten method with heteroskedastic panels corrected standard errors (PCSE). The same procedure was applied to the B1 specification. All results are stable and available from authors upon request.

Critical values tabulated by Stock and Yogo (2005) are well below the reported value.

When both current and lagged degrees of vertical disintegration are included in the equation, only the former have a significant effect on the inefficiency level and the magnitude is in line with that of specification B1. Results are available from the authors upon request.

Note that the result in specification B3 is not due to sample bias, passing from 2,973 to 2,555 observations; in fact, re-running specification B1 on the sample of B3 by means of OLS, the VDIS_it elasticity becomes almost 0.13%. Results are available from the authors upon request.

The assumption of higher fixed organizational costs for integrated firms relates to the additional managerial tasks needed to supervise intermediate stages of the production process; this hypothesis seems reasonable in the MT industry, in which some activities, such as the production of mechanical components or electronic assemblies, require not negligible supervision and coordination efforts.

Both the TFE and TREMU models are difficult to be estimated with the parameterized variance of the inefficiency distribution and may result in unreliable estimates of the coefficients. Following Greene (2008), we performed the one-step estimation with the TFE model: to our knowledge, there are no applications of TREMU with third variables affecting the parameters of the inefficiency distribution. We do not report the frontier parameters in specifications C1 and C2 for reasons of space. Complete results are available from authors upon request.

See the ISTAT web page, http://www.istat.it/conti/nazionali.

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Titel: Vertical integration and efficiency: an application to the Italian machine tool industry
verfasst von: Fabio Pieri
Enrico Zaninotto
Publikationsdatum: 01.02.2013
Verlag: Springer US
Erschienen in: Small Business Economics / Ausgabe 2/2013
Print ISSN: 0921-898X
Elektronische ISSN: 1573-0913
DOI: https://doi.org/10.1007/s11187-011-9367-y

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