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A ray of hope? Another look at the Italian textile industry

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Abstract

Despite increasing competition from newly industrializing countries, Italy’s textile industry has continued to be an important contributor to the domestic economy. Many observers attribute this resilience to the industry’s focus on quality. Here, we take note of that view but also examine production and cost relationships to explore the existence of returns to scale and the interrelationships among inputs to gain additional insights about the future prospects for this industry. The findings are consistent with constant returns to scale and a substitute relationship between all input pairs except for domestic capital and foreign intermediate goods. The results also suggest some increasing flexibility in the labor market, perhaps including informal sector arrangements, greater responsiveness of labor demand to the price of capital, and more international production sharing arrangements. An increasing elasticity over time of the demands for domestic capital and domestic intermediate goods with respect to the price of foreign substitutes was also observed. Since further economies of scale do not exist, maintaining the Italian textile industry’s reputation for outstanding quality will likely be an important survival strategy for some products. For others, production sharing may be necessary to maintain international competitiveness.

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Notes

  1. While the liberalization was scheduled in stages, much of it was delayed until 2005, so the January 1, 2005 date was particularly significant (Liu and Sun 2004, pp. 53–54). However, the ATC also included some provisions that enabled countries to at least temporarily still place restrictions on textile and apparel imports. One example is the arrangement that admitted China to the WTO included a provision that allowed the other members to place restrictions on all imports subject to the ATC until 2008, as well as a China-specific measure that is effective until 2013 (Liu and Sun 2004, p. 54). The United States did determine that resulting increases in imports in early 2005 were disrupting domestic markets and reimposed limits on imports of some Chinese textiles in April of that year (Federal Reserve Bank of Atlanta 2005, p. 13).

  2. Istituto Nazionale di Statistica, Annuario statistico italiano: 2006, pp. 422–423.

  3. Istituto Nazionale di Statistico (2010), Commercio estero e attività internazionali delle imprese: 2009, pp. 167–187.

  4. See Istituto Nazionale di Statistica (Annuario statistico italiano: 2006, 1995–2009; Istituto Nazionale di Statistica (Annuario statistico italiano: 2009, 1995–2009; Istituto Nazionale di Statistica, Contabilità nazionale, Tomo I, 2005; and Istituto Nazionale di Statistica, Contabilità nazionale, 2007.) The official statistics likely do not reflect the total economic impact of this industry as a result of the existence of an active informal or “underground” economy in this industry (Aniello 2001). Moreover, while the employment statistics include both self-employed workers and employees, payments to labor appear to include only payments to employees. We have no data that would allow us to even approximately estimate the earnings of workers in the informal sector. Since separate textile industry data are also not available for the returns to the self-employed, there is no basis to impute part of industry profit to wages.

  5. Some of these studies include (Aniello 2001; Antonelli and Marchionatti 1998; Berra et al. 1995; Bolisani and Scarso 1996; Camagni and Rabellotti 1992; De Robertis 2001; De Toni and Meneghetti 2000; Guercini 2004; Guercini and Runfola 2004; Owen and Jones 2003).

  6. See, for example, (Owen and Jones 2003, especially Chapter 3; Bolisano and Scarso 1996, especially p. 72; and Berra et al. 1995).

  7. See Jorgenson (2000, Chap. 4),and Greene (2000, pp. 640–644) for more detailed discussions of translog functions. Also see Kohli (1991, pp. 103–106) for a discussion of the technological change variable.

  8. The principal advantages of using a translog cost function rather than a translog production function are found in the following features of the cost function: (1) the partial derivatives of a cost function with respect to input prices yield the corresponding input demand functions (Shephard’s Lemma), (2) it follows from (1) that the partial derivative of the cost function in logarithmic form with respect to factor prices yields the cost shares, and (3) the partial derivative of the cost function in logarithmic form with respect to output yields the cost elasticity with respect to output level (Jorgenson 2000, Chapter 1).

  9. See Christensen and Greene (1976, p. 661). A cost function corresponds to a homothetic production function if and only if the former function is separable with respect to output and the input prices. A homogeneous production function also requires that the elasticity of cost with respect to output be constant.

  10. The intermediate goods category includes all semi-processed goods, raw materials, and energy purchased by the industry. We know of no available times series data for the industry that break down intermediate goods purchases into more detailed categories.

  11. As a referee pointed out, a perhaps preferable approach to estimating a return to capital is to utilize appropriate capital stock data, if it were available, to derive an ex-post rate of return on capital.

  12. The likelihood ratio, \(\lambda \), is the ratio of the maximum value of the likelihood function with restrictions imposed over the maximum value of the likelihood function without restrictions. Theil (1971, p. 397) has shown that \(-2 {\text{ ln}} \lambda \) is distributed asymptotically as \(\chi ^{2}\) with degrees of freedom equal to the number of independent restrictions imposed. Seven restrictions were imposed as we moved from the initial model to the final model.

  13. The conventional single-equation Durbin–Watson (1957 and Malinvaud 1970, p. 509) statistic for the total cost function was 2.31, in the inconclusive range at the 5 % level of significance.

          A Lagrange multiplier test for serial correlation was also done on the total cost equation using lagged values of the error term ranging from one to nine periods (see Godfrey 1988, pp. 112–117; and Greene 2000, pp. 540–541). The null hypothesis of \(\rho =\) 0 could not be rejected at the 5 % percent level of significance for any of the lag specifications.

          In addition, the regression specification error test (RESET) was performed on the total cost equation using terms involving the dependent variable estimates up to the fourth power (Maddala 1992, p. 478). This procedure did not suggest any model specification errors at the 5 % percent level of significance.

  14. The direct price elasticity and cross price elasticity formulas used in this paper are the conditional elasticities (Uzawa 1962).

  15. See Aniello (2001) for a discussion of how small and medium-sized firms in the industry achieve labor market flexibility. Owen and Jones (2003, p. 28) also relate how the Prato firms increase labor flexibility by establishing companies with fewer than 15 employees.

  16. See Berra et al. (1995) and Bolisani and Scarso (1996) for a discussion of foreign substitutes for domestic labor in the Italian apparel industry.

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Acknowledgments

The authors wish to thank Dr. Hamid Beladi and two anonymous referees for many helpful comments and suggestions. This research was partially supported by a University of Texas at San Antonio College of Business Summer Research Grant. An earlier version was previously published as The University of Texas at San Antonio, College of Business, Working Paper Series, Wp# 0060ECO-102-2008.

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  1. Department of Economics, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX, 78249-0633, USA

    Lila J. Truett & Dale B. Truett

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  1. Lila J. Truett
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  2. Dale B. Truett
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Correspondence to Lila J. Truett.

Appendix

Appendix

See Tables 5 and 6.

Table 5 Textile industry output and input price data
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Table 6 Textile industry input shares
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Truett, L.J., Truett, D.B. A ray of hope? Another look at the Italian textile industry. Empir Econ 46, 525–542 (2014). https://doi.org/10.1007/s00181-013-0681-x

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