The impact of immigration on output and its components: a sectoral analysis for Italy at regional level


This paper studies the impact of immigrant workers on Italian sectors. The analysis is based on the channel output decomposition approach, by means of which the effect of immigration is measured with respect to per capita value added and its components. The empirical investigation is carried out at sector level during the period 2008–2011. The results show that immigrants exert a positive impact on total output which is mainly driven by the effect on total factor productivity. The main finding is that not all sectors benefit from the productivity gains. The sectors that mostly take advantage of immigrant workers are those featured by the predominance of manual tasks not requiring high communication skills.

This is a preview of subscription content, log in to check access.


  1. 1.

    This index combines more and less educated workers in a constant elasticity of substitution function where the elasticity of substitution is bounded to be higher than zero.

  2. 2.

    Unioncamere (Italian Union of Chambers of Commerce, Industry, Handicraft and Agriculture) is a public institution that represents the Italian Chamber system.

  3. 3.

    These estimates consider both regular and irregular employment.

  4. 4.

    Italian regions are 20, but ISTAT merges the data of the smallest one, that is Valle D’Aosta, with the neighbouring Piemonte.

  5. 5.

    The empirical model in Eq. (5) could be seen as a linear system of equations. Accordingly, it might be estimated using seemingly unrelated regressions (SUR) in order to gain efficiency from taking account of correlation between error terms across equations. However, it can be demonstrated that when the same regressors appear in the right hand side of each equation (i.e. our case), estimating the model using OLS equation by equation is equivalent to SUR (see for instance Wooldridge 2010).

  6. 6.

    Dropping the interaction terms, the Eq. (5) simplifies to \(lnb_{irt} = d_{i} + d_{r} + d_{t} + \gamma_{b} z_{irt} + \varepsilon_{irt}\).

  7. 7.

    This value is within the range of values (i.e., 0.29 and 0.36) estimated for Italy by Marrocu and Paci (2010).

  8. 8.

    The 2002 is the first year for which data of immigrants by country of origin are available at regional level. Usually the lagged year goes back a couple of decades, however immigration in Italy has experienced some important shocks in both the paths and trends of international immigration between 2002 and 2007 which can justify the adoption of this short lag. The main source of these shocks is the enlargement of the EU to central and eastern European countries.

  9. 9.

    For each region we average the shortest road-distances across all province capital cities. Different road types are considered, not only highways.

  10. 10.

    The number of workers in year t (by region and industry) is constructed as the average of total workers in each quarter. Self employed are not considered.

  11. 11.

    We have used the variable ORELAV which measures the hours worked in a week and multiplied it by 13 (i.e. the average number of weeks in a quarter) to obtain the total number of hours worked in each quarter and then we computed the sum to obtain the total number of hours worked in year t. Hours per worker, for both natives and immigrants in each education cell, is computed as the ratio of total hours worked in year t (by region and industry) to the corresponding total number of workers.

  12. 12.

    The industry weights are constructed with respect to each industry, so that the sum of the weights for each industry over the 19 regions is equal to one.

  13. 13.

    For each quarter we multiply (for each type of worker) the variable RETRIC by COEFF and by three and then take the sum by region and industry. We then sum all the quarters’ pays to obtain the annual pay. The annual pay is then divided by average number of workers in order to obtain the average pay per worker, which is finally divided by the annual hours worked by high (low) skilled worker in region r, industry i and year t.

  14. 14.

    Unfortunately the data do not allow a further disaggregation.

  15. 15.

    The Stock and Yogo (2005) critical values are available only for models including up to two endogenous regressors. For this reason, the statistics has not been computed for the models with the interaction terms.


  1. Accetturo, A., Bugamelli, M., & Lamorgese, A. (2012). Welcome to the machine: Firms’ reaction to low-skilled immigration (p. 846). Temi di discussione N: Banca d’Italia.

    Google Scholar 

  2. Aleksynska, M., & Tritah, A. (2015). The heterogeneity of immigrants, host countries’ income and productivity: A channel accounting approach. Economic Inquiry, 53, 150–172.

    Article  Google Scholar 

  3. Alesina, A., Harnoss, J., & Rapoport, H. (2016). Birthplace diversity and economic prosperity. Journal of Economic Growth, 21, 101–138.

    Article  Google Scholar 

  4. Altonji, J. G., & Card, D. (1991). The effects of immigration on labor market outcomes of less-skilled natives. In J. Abowd & R. Freeman (Eds.), Immigration, trade, and labor markets (pp. 201–234). Oxford: Elsevier.

    Google Scholar 

  5. Bank of Italy. (2006, 2007). Indagine sul turismo internazionale dell’Italia. Retrieved in September 2016, from Bank of Italy web site.

  6. Bettin, G., Lo, Turco A., & Maggioni, D. (2014). A firm-level perspective on migration. The role of extra-EU workers in Italian manufacturing. Journal of Productivity Analysis, 42, 305–325.

    Article  Google Scholar 

  7. Blankenou, W. F., & Cassou, S. P. (2011). Industry estimates of the elasticity of substitution and the rate of biased technological change between skilled and unskilled labour. Applied Economics, 43, 3129–3142.

    Article  Google Scholar 

  8. Borjas, G. J. (2014). Immigration economics. Massachusetts: Harvard University Press.

    Google Scholar 

  9. Borjas, G. J., Grogger, J., & Hanson, G. H. (2012). Comment: On estimating elasticities of substitution. Journal of the European Economic Association, 10, 198–210.

    Article  Google Scholar 

  10. Card, D. (2001). Immigrant inflows, native outflows, and the local market impacts of higher immigration. Journal of Labor Economics, 19, 22–64.

    Article  Google Scholar 

  11. Ciccone, A., & Peri, G. (2005). Long-run substitutability between more and less educated workers: Evidence from US states, 1950–1990. The Review of Economics and Statistics, 87, 652–663.

    Article  Google Scholar 

  12. Cortes, P. (2008). The effect of low-skilled immigration on US prices: Evidence from CPI data. Journal of Political Economy, 116, 381–422.

    Article  Google Scholar 

  13. De Arcangelis, G., Di Porto, E., & Santoni, G. (2015a). Immigration and manufacturing in Italy. Evidence from the 2000s. Economia e Politica Industriale, 42, 163–187.

    Article  Google Scholar 

  14. De Arcangelis, G., Di Porto, E., & Santoni, G. (2015b). Migration, labor tasks and production structure. Regional Science and Urban Economics, 53, 156–169.

    Article  Google Scholar 

  15. Dustmann, C., Schönberg, U., & Stuhler, J. (2016). The impact of immigration: Why do studies reach such different results? Journal of Economic Perspectives, 30, 31–56.

    Article  Google Scholar 

  16. Etzo, I., Massidda, C., & Piras, R. (2015). The impact of immigrants settlements’ on Italian firms. Paper presented to Italian Economic Association, 56th Annual Conference, Naples (Italy) 22–24 October 2015.

  17. Falzoni, A. M., Venturini, A., & Villosio, C. (2011). Skilled and unskilled wage dynamics in Italy in the 1990s: Changes in individual characteristics, institutions, trade and technology. International Review of Applied Economics, 25, 441–463.

    Article  Google Scholar 

  18. Gonzales, L., & Ortega, F. (2013). Immigration and housing booms: Evidence from Spain. Journal of Regional Science, 53, 37–59.

    Article  Google Scholar 

  19. Hall, R. E., & Jones, C. I. (1999). Why do some countries produce so much more output per worker than others? Quarterly Journal of Economics, 114, 83–116.

    Article  Google Scholar 

  20. Hunt, J. (2011). Which immigrants are most innovative and entrepreneurial? Distinctions by entry visa. Journal of Labor Economics, 29, 417–457.

    Article  Google Scholar 

  21. Kerr, W. R., & Lincoln, W. F. (2010). The supply side of innovation: H-1b visa reforms and US ethnic invention. NBER working paper N. 15768.

  22. Kleibergen, F., & Paap, R. (2006). Generalized reduced rank tests using the singular value decomposition. Journal of Econometrics, 133, 97–126.

    Article  Google Scholar 

  23. Lewis, E. G. (2011). Immigration, skill mix, and capital skill complementarity. Quarterly Journal of Economics, 126, 1029–1069.

    Article  Google Scholar 

  24. Lewis, E. G., & Peri, G. (2015). Immigration and the economy of cities and regions. In G. Duranton, V. J. Henderson, & W. C. Strange (Eds.), Handbook of regional and urban economics (Vol. 5, pp. 625–685). Oxford: Elsevier.

    Google Scholar 

  25. Marrocu, E., & Paci, R. (2010). The effects of public capital on the productivity of the Italian regions. Applied Economics, 42, 989–1002.

    Article  Google Scholar 

  26. Mazzolari, F., & Neumark, D. (2012). Immigration and productivity diversity. Journal of Population Economics, 25, 1107–1137.

    Article  Google Scholar 

  27. Mocetti, S., & Porello, C. (2010). How does immigration affect native internal mobility? New evidence from Italy. Regional Science and Urban Economics, 40, 427–439.

    Article  Google Scholar 

  28. Moressa, Fondazione. (2016). Rapporto annuale sull’economia dell’immigrazione. Il Mulino, Bologna: L’impatto fiscale del’immigrazione.

    Google Scholar 

  29. Murat, M., & Paba, S. (2004). International migration, outsourcing, and Italian industrial districts. Materiali di discussione. Università di Modena e Reggio Emilia.

  30. Olney, W. (2013). Immigration and firms expansion. Journal of Regional Science, 53, 142–157.

    Article  Google Scholar 

  31. Ortega, F., & Peri, G. (2009). The causes and effects of international migration: Evidence from OECD countries 1980–2005. NBER Working Papers N. 14833.

  32. Ottaviano, G. I. P., & Peri, G. (2006). Rethinking the gains from immigration. Theory and evidence from USA. FEEM Working Paper N. 52.

  33. Ottaviano, G. I. P., & Peri, G. (2008). Immigration and national wages: Clarifying the theory and the empirics. NBER Working Papers N. 14188.

  34. Ottaviano, G. I. P., & Peri, G. (2012). Rethinking the effect of immigration on wages. Journal of the European Economic Association, 10, 152–197.

    Article  Google Scholar 

  35. Ottaviano, G. I. P., & Peri, G. (2013). New frontiers of immigration research: Cities and firms. Journal of Regional Science, 53, 1–7.

    Article  Google Scholar 

  36. Peri, G. (2012). The effect of immigration on productivity: Evidence from US States. The Review of Economics and Statistics, 94, 348–358.

    Article  Google Scholar 

  37. Peri, G., & Sparber, C. (2009). Task specialization, immigration, and wages. American Economic Journal Applied Economics, 1, 135–169.

    Article  Google Scholar 

  38. Romiti, A. (2011). Immigrants-natives complementarities in production: Evidence from Italy. CERP Working Paper N. 105.

  39. Staffolani, S., & Valentini, E. (2010). Does immigration raise blue and white collar wages of natives? The case of Italy. Labour, 24, 295–310.

    Article  Google Scholar 

  40. Stock, J. H., & Yogo, M. (2005). Testing for weak instruments in linear IV regression. In D. W. K. Andrews & J. H. Stock (Eds.), Identification and inference for econometric models: Essays in honor of Thomas Rothenberg (pp. 80–108). Cambridge: Cambridge University Press.

    Google Scholar 

  41. Unioncamere. (2014). Audizione dell’Unioncamere—Comitato parlamentare di controllo sull’attuazione dell’accordo di Schengen, di vigilanza sull’attività di Europol, di controllo e vigilanza in materia di immigrazione, 20 March 2014.

  42. Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data (2nd ed.). Cambridge: The MIT Press.

    Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Ivan Etzo.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Etzo, I., Massidda, C., Mattana, P. et al. The impact of immigration on output and its components: a sectoral analysis for Italy at regional level. Econ Polit 34, 533–564 (2017).

Download citation


  • Channel output decomposition approach
  • Immigrant workers
  • Italy
  • Sectors
  • Regions

JEL Classification

  • F22
  • F62
  • J61