Outsourcing and firm Outsourcing and firm performance in the Italian performance in the Italian manufacturing industrymanufacturing industry

Pinuccia Calia, Silvia PaceiDipartimento di Scienze Statistiche

Università di Bologna

L’analisi dei dati di impresa per la conoscenza del sistema produttivo italiano: il

ruolo della statistica ufficiale21-22 novembre 2011

Istat - Roma

Motivation (1)Motivation (1) Fragmentation of production has increased without

precedent in the last two decades, boosted by: - diffusion on ICT that made it possible to perform activities in any location (Grossman and Helpman 2005);- continuous decline of transportation costs that has facilitated the worldwide flows of goods (Hummels 2007).

The fragmentation of production has more and more often gone beyond the boundaries of the firm, so as to involve other independent firms.

In this case we can speak about “outsourcing”.

If the outside supplier is an offshore company we speak about international outsourcing or off-shoring

Motivation (2) Motivation (2) The scope of outsourcing is :

- to take advantage of specialization and scale economies in production tasks by specialized suppliers ;- to gain flexibility to respond to demand changes quickly.

As a consequence, firms may specialize in those activities where they have a competitive edge seeking to improve production efficiency, and consequently, their competitiveness (Dìaz-Mora, 2008).

The fundamental question is whether outsourcing is value enhancing and, in particular, whether firms undertaking outsourcing benefit higher productivity and profitability.

Theoretical frameworkTheoretical framework Grossman and Helpman (2002) provide a comprehensive

analysis of firms’ outsourcing decision, building on transaction cost theory (Williamson 1975, 1985) and property right theory (Grossman and Hart, 1986).

Outsourcing entails a variety of transaction costs that arise from the need of asset specific investment and the specification, monitoring and enforcement of contracts.

On the contrary, outsourcing increases the flexibility in the production process as well as it allows to benefit from provider cost advantages derived from specialization, experience, economies of scale and location.

Outsourcing is attractive only when transaction costs incurring from asset specificity, incomplete contracting and search efforts are lower than the production costs advantage.

Benefits of outsourcingBenefits of outsourcing Outsourcing allows access to better, cheaper and

more varied (final and intermediate) inputs, because goods and services may be more efficiently produced by other firms and bought at a lower prices.

The benefits of outsourcing on productivity and profitability derives principally form savings resources in terms of both labor costs and capital

However it is an unresolved empirical issue whether outsourcing actually has a positive influence on a firm’s performance as is expected a priori.

DataData Firm-level panel that put together data collected

in different surveys and administrative archives (SCI, PMI, balance sheets archives)

Years 1998-2007 Target population: enterprises in industry and

service sectors with twenty or more employees. Catch-up prospective panel: starting from firms

surveyed in 1998 and then locating firms in the present by subsequent observation.

New firms entering after 1998 are not included. Only firms which, after 1998, are survey

respondent or are present in the BS archives at least for 4 years are included.

We select manufacturing firms: 8,235 in 1998, 5,862 in 2007 with complete information.

Measures of outsourcingMeasures of outsourcing We measure outsourcing by “works contracted out to third

parties on raw materials supplied to them” which refers to tasks which being a part of the own production process are carried out by other firms.

Neither external services nor purchases of raw materials and supplies (office materials or fuel,) are included.

Subcontracts are included within this concept. This measure overcome the shortages implied by

outsourcing measured as the value of material intermediate inputs:

- it includes raw material purchases and arms-length purchases of standardized components in the market (Diaz-Mora, 2008).

- it does not capture the outsourcing of the final production stage, the assembly or specific production tasks.

Indicators of outsourcing Indicators of outsourcing intensityintensity 1) The ratio of the value of outsourcing to the

number of employees of the firm;

2) The ratio of the value of outsourcing to the total wage bill of the firm. Outsourcing can be seen as a substitute for in-house production and hence may, in the short run, lead to a reduction in the total wage bill: the cost of outsourcing may be seen as the opportunity wage that would have occurred to in-house employees if these services had not been contracted out (Girma and Gorg, 2004).

The two are related by a factor equal to the wage rate.

Measures of performanceMeasures of performance Productivity indicator: labor productivity

- ratio of operational value added to the number of employees.

Profitability indicator: “per capita gross earnings before taxation”- ratio of EBITDA (the difference between value added and labor costs) to the number of employees (Görzig and Stephan, 2002; Giannelle and Tattara, 2009).

Some summary statistics Some summary statistics (1)(1)The percentage of firms which outsource

range between 70% and 74% across years.

Neither all the firms that start to outsource continue in the next years nor the outsourcing firms are the same every year

Considering the pure panel (60% of all the firms in 1998):- 23% of firms outsource every year - 19% outsource almost all the years but one. - 3% of firms never outsource, - 54% follows all the other patterns of behaviour

Year

 

OutsourcingFirms

OutsourcingCosts

Outsourcingcosts/

employees

Outsourcingcosts/wage bill

1998 Mean 0.71 2441.17 13.34 0.46Cv 0.64 4.28 1.70 1.70

1999 Mean 0.72 2551.69 13.55 0.45Cv 0.63 4.28 1.64 1.64

2000 Mean 0.70 2641.78 13.98 0.47Cv 0.66 4.28 1.70 2.58

2001 Mean 0.71 2972.38 14.25 0.46Cv 0.64 4.41 1.63 1.53

2002 Mean 0.71 2698.86 14.32 0.45Cv 0.64 3.50 1.74 1.65

2003 Mean 0.74 2745.31 14.17 0.44Cv 0.60 3.54 1.65 1.58

2004 Mean 0.73 2519.16 13.96 0.43Cv 0.61 2.97 1.62 1.56

2005 Mean 0.71 2650.14 14.15 0.43Cv 0.64 3.60 1.55 1.50

2006 Mean 0.71 2631.57 14.14 0.43Cv 0.64 3.33 1.63 1.55

2007 Mean 0.72 2905.31 15.15 0.45Cv 0.62 3.26 1.57 1.46

Table 1: Outsourcing firms, outsourcing costs, and outsourcing intensity: mean and CV by year

Some summary statistics Some summary statistics (2)(2)Outsourcing/employees increases slightly

every yearOutsourcing/wage bill remains almost

constant and decreases a bit after 2002.

The number of employees tends to remain almost stable across years while the wage bill increases steadily, due to the increase in wage rate

EBITDA /employee stays more or less constantEBITDA /wage bill declines steadily till the last

year considered. Labor productivity, on the contrary, is

constant through the period

Table 2: Performance and other characteristics: mean and CV by year

YearLabor

productivity

EBITDA/employe

es

EBITDA/ wage bill

Numberof

employees

Wage bill

Wage Rate

CapitalIntensit

y

1998Mea

n 51.50 21.19 0.69 194.64 6936.08 30.32 44.92Cv 0.68 1.47 1.33 3.10 3.84 0.33 1.32

1999Mea

n 51.04 19.69 0.63 199.06 7235.34 31.35 45.53Cv 0.72 1.64 2.22 2.91 3.49 0.36 1.25

2000Mea

n 51.81 20.48 0.66 205.09 7336.21 31.33 50.08Cv 0.96 2.31 3.70 2.95 3.38 0.32 1.20

2001Mea

n 50.72 19.32 0.60 205.91 7380.57 31.40 49.72Cv 0.75 1.82 1.53 2.91 3.33 0.32 1.19

2002Mea

n 51.17 18.57 0.56 203.46 7491.97 32.60 50.18Cv 0.66 1.59 1.41 2.74 3.15 0.35 1.22

2003Mea

n 50.82 17.53 0.51 204.08 7690.87 33.28 64.08Cv 0.72 1.87 1.62 2.79 3.14 0.33 13.27

2004Mea

n 51.15 17.65 0.50 204.71 7797.08 33.51 64.04Cv 0.72 1.89 1.85 2.72 3.05 0.33 11.28

2005Mea

n 51.05 17.42 0.49 202.51 7650.35 33.63 52.66Cv 0.87 2.37 1.96 2.78 3.20 0.35 1.50

2006Mea

n 51.33 17.38 0.48 205.84 7831.16 33.95 55.87Cv 0.72 1.94 1.75 2.76 3.13 0.34 2.47

2007Mea

n 543.49 19.36 0.54 210.07 8057.47 34.14 56.45Cv 0.80 2.04 1.81 2.76 3.14 0.33 3.88

Year EBITDA / wage bill EBITDA / employees Labor productivity

No Outs. Outs. No Outs. Outs. No Outs. Outs.

1998 0.74*** 0.67 23.72*** 20.15 54.87*** 50.12

1999 0.67* 0.61 22.15*** 18.73 54.08*** 49.85

2000 0.67 0.65 21.85** 19.88 53.79** 50.95

2001 0.66*** 0.58 21.54*** 18.42 53.34*** 49.66

2002 0.62*** 0.53 21.34*** 17.44 54.74*** 49.72

2003 0.62*** 0.48 21.48*** 16.12 55.35*** 49.20

2004 0.58*** 0.47 20.32*** 16.65 54.30*** 49.97

2005 0.55*** 0.46 20.65*** 16.12 54.55*** 49.64

2006 0.52** 0.47 19.14*** 16.65 53.41** 50.46

2007 0.63*** 0.51 22.50*** 18.15 56.93*** 52.18

Table 3: Productivity and profitability indicators, by year and outsourcing status

Note: difference in means significant at: *** 1%, ** 5%, * 10%

Some summary statistics Some summary statistics (3)(3)Non outsourcing firms exhibit higher

average capital intensity but smaller size: outsourcing firms seem more labor-intensive.

Non outsourcing firms exhibit lower average total wage bill but higher wage rates (at least until 2004).

Year Capital intensity

Number of employees

Wage bill Wage rate

No Outs. Outs. No Outs. Outs. No Outs. Outs. No Outs. Outs.1998 56.36*** 40.25 174.11** 203.08 6484.63 7121.54 31.15*** 29.97

1999 55.25*** 41.78173.66**

* 209.006459.49

** 7538.80 31.93*** 31.12

2000 61.08*** 45.33180.56**

* 215.806728.28

* 7601.71 31.94** 31.07

2001 61.21*** 45.10168.65**

* 221.056157.43

*** 7877.62 31.80** 31.24

2002 63.43*** 44.88 180.18** 212.936822.34

* 7764.52 33.40*** 32.28

2003 74.02*** 60.58158.41**

* 220.366063.23

*** 8271.10 33.87*** 33.08

2004 67.41*** 62.80175.04**

* 215.816782.83

** 8176.82 33.98** 33.33

2005 67.45*** 46.78161.99**

* 212.356246.30

*** 8218.32 33.90 33.52

2006 69.40*** 50.32 179.48** 210.517195.05

* 8094.13 34.27* 33.81

2007 75.90*** 49.10175.33**

* 217.766971.51

** 8473.61 34.43 34.03

Table 4: Capital intensity, size, wage bill, and wage rate, by year and outsourcing status

Note: difference in means significant at: *** 1%, ** 5%, * 10%

Wave

Productivity EBITDA/employees 

Class of outsourcing costs per employees

Class of outsourcing costs per employees

No Outs.

0ǀ2.5 2.5ǀ7 7ǀ17 more than 17

No Outs.

0ǀ2.5 2.5ǀ7 7ǀ17 more than 17

1998 54.87 48.0 47.4 49.5 56.4 23.72 18.9 17.8 19.5 24.9

1999 54.08 46.8 46.6 48.7 57.9 22.15 17.2 16.0 17.6 24.5

2000 53.79 49.2 47.6 48.8 58.2 21.85 19.6 17.1 17.7 25.1

2001 53.34 46.5 46.2 47.4 58.2 21.54 16.5 15.7 16.3 24.9

2002 54.74 48.2 47.8 47.0 56.0 21.34 16.7 16.2 15.4 21.4

2003 55.35 48.4 46.6 48.0 53.9 21.48 16.5 14.1 15.0 18.9

2004 54.30 48.0 47.2 48.2 56.7 20.32 15.8 14.5 15.2 21.2

2005 54.55 46.9 47.6 47.7 56.3 20.65 14.4 15.1 14.4 20.6

2006 53.41 48.3 47.3 48.1 58.3 19.14 15.6 14.2 14.7 22.2

2007 56.93 50.8 48.4 49.7 58.9 22.50 17.5 15.2 16.0 23.2

Table 5: Productivity and profitability indicators by classes of outsourcing intensity and year (thousands of euros)

Econometric analysis – The Econometric analysis – The modelmodelGeneral equation of performance indicator augmented by a measure of “outsourcing intensity” at the firm level:

[1]

where

is the performance measure for firm i at time t; is a vector of time variant controls variables; is the outsourcing intensity; are individual time-invariant effects; are time effects; are error terms.

We use the longitudinal structure of the data to estimate alternative model based on different identifying assumptions.

niTt ucintouty ittiititit ,...,1;,...,1 βx

ity

itx

itintout

ic

t

itu

Econometric analysis – FDEconometric analysis – FDAssuming outsourcing depends on unobservable individual-specific effects and no restrictions are imposed on correlation between and covariates, we are in the fixed-effect framework and we may use a first difference transformation;

[2]

where time, sector and regional dummies are introduced.

The above equation is estimeted by OLS (FD).

A way to allow for a more general dependence between outsourcing and unobservable heterogeneity is to introduce in model [1] an additional source of heterogeneity as an individual specific time trend.

n,...,i;T,...,titrstititit uDDDintoutxy 12

Econometric analysis – RGMEconometric analysis – RGMIn the Random Growth Model (RGM), each individual (firm) is allowed to have its own time trend.

[3]

In this case we assume outsourcing depends on unobservable individual-specific (time invariant) growth rates in addition to the level effects

Applying second difference eliminates and :

[4]

Parameters and may be estimated by OLS.

niTt ittiiititit utgcouty ,...,1;,...,1int βx

ic

ic

ig

niTt itrstititit uDDDouty ,...,1;,...,32222 int βx

β

Econometric analysis – IVEconometric analysis – IV

Consistency of both estimators relies heavily on the strict exogeneity assumption (Wooldridge, 2002, 2005).

Potential endogeneity problem of the outsourcing variable: there may be unobserved time-varying factors, correlated with both performance and outsourcing intensity.

A general approach to estimate models [1] that do not satisfy the strict exogeneity assumption is to carry out a transformation to remove , and next, use instrumental variables (IV)

The issue on the validity of instruments is particularly relevant in IV estimation method. Tests to determine whether a outsourcing must be treated as endogenous and whether instruments are valid have to be used.

ic

Econometric analysis – IVEconometric analysis – IVWe choose instruments for outsourcing intensity

among the following variables (in logarithm)

- skilled and unskilled wages rates - white collar ratio,

either calculated as second differences and lagged differences

We consider the three above estimation strategies: FD, RGM and IV.

All models are estimated using a robust methods for standard errors to allow for heteroskedasticity as well as an unspecified correlation within but not across firm’s error terms.

Results - ProductivityResults - Productivity

Dependent variable: log of labor productivity.

Covariates: log of capital intensity; log of size; log of outsourcing per employees; time, sector and territorial repartition dummies.

Instruments for outsourcing: second difference of the log of wage rate for skilled and unskilled workers.

IV Estimates results: all coefficients are significant. The elasticity of labor productivity with respect to outsourcing is 0.88%.

FD and RGM results: same sign observed for IV but much smaller values. Similar results between FD and RGM.

Variables IV Estimator Random growth model

FD estimator

Outsourcing Intensity

0.8847***(0.1748)

0.0051***(0.001)

0.0064***(0.001)

Size-0.1152**(0.0549)

-0.4349***(0.0492)

-0.2723***(0.0339)

Capital intensity

0.0293**(0.0124)

0.0351***(0.007)

0.0566***(.007)

ENDOGENEITYRobust score chi2(1)p-value

132.76(0)

Robust regression F(1,49686)p-value

141.71(0)

INSTRUMENTS’ VALIDITY

F(first-stage) F(2,49687)p-value

13.441(0)

Woldridge robust score testp-value

.6149(0.433)

Observations 49,722 49,296 58,353

Table 6: Labor Productivity and Outsourcing: IV, RGM , and FD (Pooled OLS) Estimates

Results - ProfitabilityResults - ProfitabilityDependent variable: log of EBITDA per employees.

Covariates: log of capital intensity; log of size; log of outsourcing per employees; time, sector and territorial repartition dummies.

Instruments for outsourcing: second difference of -log of wage rate for skilled workers -log of white collar ratio.

IV Estimates results: The outsourcing intensity has a negative but not significant effect on profitability. Between the two components of the value added (EBITDA and labor costs) outsourcing affects mainly the labor costs per employee.

FD and RGM results: effect of outsourcing is positive (even if very small) and significant. Similar results between FD and RGM.

Table 6: Labor Profitability and Outsourcing: IV, RGM , and FD (Pooled OLS) Estimates

Variables IV Random growth rate

FD (Pooled OLS)

Outsourcing Intensity

-0.1992(0.114)

0.0071**(0.003)

0.0074***(0.003)

Size-0.4542***

(0.048)-0.4918***

(0.040)-0.3951***

(0.031)Capital intensity

0.0338***(0.009)

0.0098(0.009)

0.0341***(0.009)

ENDOGENEITYRobust score chi2(1)p-value

3.879(0.0489)

Robust regression F(1,49686)p-value

3.920(0.0477)

INSTRUMENTS’ VALIDITY

F(first-stage)p-value

12.274(0)

Woldridge robust score testp-vale

0.2868(0.592)

Observations 43,936 42,420 51,791

ConclusionsConclusions Importance of longitudinal data at firm level:

- to take account of firm’s heterogeneity- to treat endogeneity in estimating the effect of outsourcing

This preliminary analysis produces results that need to be further investigated (better model specification, separate analysis by industry).

In particular, at the moment we neglect the analysis of dynamics of outsourcing and its effect on firms’ performance, i.e. whether outsourcing firms gets a better performance after the decision to outsource.

Some referencesSome references Díaz-Mora, C. (2008) “What factors determine the outsourcing

intensity? A dynamic panel data approach for manufacturing industries”. Applied Economics, vol. 40, 2509–2521.

Gianelle, C., & Tattara, G. (2009). Manufacturing abroad while making profits at home: the Veneto footwear and clothing industry. In M. Morroni (ed.), Corporate Governance, Organization and the Firm. Co-operation and Outsourcing in the Global Economy, Cheltenham, UK: Edward Elgar.

Girma, S. and Gorg, H. (2004) Outsourcing, foreign ownership and productivity: evidence from UK establishment level data, Review of International Economics, 12, 817–32.

Görzig, B., & Stephan, A. (2002). Outsourcing and Firm-Level Performance. German Institute for Economic Research, Discussion Paper 309.

Grossman, G.M., & Helpman, E. (2005). Ousourcing in a Global Economy. Review of Economic Studies, 72(250), 135-159.

Hummels, D. (2007). Transportation Costs and International Trade in the Second Era of Globalization. Journal of Economic Perspectives, 21(3), 131–154.

Williamson, O. (1975) Markets and Hierarchies: Analysis and Antitrust Implications, Macmillan, New York.

Wooldridge J.M. (2002), Econometric Analysis of Cross Section and Panel Data, The MIT Press: London.