Uncertainty, Job Complexity and Pay-for
Performance: An Empirical Analysis of
Spanish Industrial Firms
January 20, 2011
Marco A. Barrenechea-Méndez (UAB)
Pedro Ortín-Angel (UAB)
Eduardo Rodes (UAB)
2011 North American Summer Meeting of the Econometric Society
Main Idea of the Paper
Organizational Design
Uncertainty
Local Private
Knowledge (Job
Complexity)
Pay-for-performance
strenght
Delegation of Decision
Making (autonomy)
Informational contexts
2011 North American Summer Meeting of the Econometric Society
What We Found?
Uncertainty
+
Autonomy
+
Pay-for-performance
-
Job
complexity
+
Autonomy
+
Pay-for-performance
NE
2011 North American Summer Meeting of the Econometric Society
Theoretical Background
Agency Model (Holmström & Milgrom 1987)
1
b
1  rC ' ' e  2


,
Given the agent is risk averse,
2
increases in Uncertainty 
makes the provision of
incentives more expensive.
Then, the principal reacts
decreasing the incentives
strength b.

2
Uncertainty
Random events -arising from
the external environment- that
adds performance
measurement error (i.e., that
randomize performance, or in
other words, that disasociate
output realizations from effort
exertion)
2011 North American Summer Meeting of the Econometric Society
Theoretical Background
However empirical evidence is inconclusive
Prendergast (2002)
Occupations
Executives
Sharecropers
Franchise
Other
Total
Papers ...
in Favour
3
0
0
1
4
Against
3
3
3
2
11
With no relationship
5
0
2
4
11
Total
11
3
5
7
26
With no relationship
7
Total
28
Devaro and Kurtulus (2010)
Occupations
All
Papers ...
in Favour
8
Against
13
2011 North American Summer Meeting of the Econometric Society
Theoretical Background
The theoretical
literature answer:
Zabojnik 1996, Adams 2002, Baker
and Jorgensen 2003, Shi 2005 and
Raith 2008
Firms’ Profits
b
Local Private
Knowledge
Random events
observed only by
the Agent that can
change his effort’s
marginal
productivity
Autonomy
Prendergast 2002
2011 North American Summer Meeting of the Econometric Society
Theoretical Background
Implicitly these models suggest is that the measures of uncertainty used in
the previous empirical literature has enveloped both the effect of
uncertainty itself and of the local private knowledge.
Alternative argument:
Nagar (2002)
In Highly volatile environments the cost for firms to acquire information for
operational decisions is high; consequently, the firms delegate decisions
to workers (who have better access to this information)
Core and Quian (2002)
Worker perform both “evaluation task” and “production task.” In the former
uncertainty has a positive effect on the provision of incentives while in the
later a negative one. If we control for a measure of evaluation task (e.g.
autonomy) we isolate the negative effect of uncertainty on incentives.
2011 North American Summer Meeting of the Econometric Society
Hypotheses
H1
Pay-for-performance strength is negatively related to
Uncertainty
H2
Pay-for-performance strength is positively related
to Job complexity
H3
Pay-for performance strength is positively related
to Autonomy
H4
H5
Autonomy is positively related to Job complexity
Autonomy is positively related to Uncertainty
(Nagar 2002)
2011 North American Summer Meeting of the Econometric Society
Previous Empirical Literature
H1
Rao (1971), Hallagan (1978), Anderson and Schmittlein (1984), Mulherin (1986),
Kawasaki and McMillan (1987), Lambert and Larcker (1987), Martin (1988),
Norton (1988), John and Weitz (1988, 1989), Leffler and Rucker (1991), Allen
and Lueck (1992), Coughlin and Narasimhan (1992), Lafontaine (1992), Garen
(1994), Allen and Lueck (1995), Yermack (1995), Bushman et al. (1996), Ittner et
al. (1997), Aggarwal and Samwick (1999, 2002), MacLeod and Parent (1999),
Core and Guay (1999, 2002), Conyon and Murphy (1999), Jin (2000), Oyer and
Shaefer (2001, 2005), Ackerber and Boticini (2002), Nagar (2002), Mengistae
and Xu (2004), Foss and Laursen 2005, Gibbs, Merchand, Van der Stede and
Vargus (2006), Devaro and Kurtulos 2010, Ben-Ner, Kong and Lluis 2010
H2
Baiman, Larker and Rajan 1995, Ortega 2009, Ben-Ner, Kong and Lluis 2010)
H3
MacLeod and Parent 1999, Adams 2002, Nagar 2002, Abernethy et al. 2004,
Foss and Laursen 2005, Moers 2006, Wulf 2007, Itoh, Kikutani and Hayashida
2008, Devaro and Kurtulos 2010, Ben-Ner, Kong and Lluis 2010
H4
Baiman, Larker and Rajan 1995, Colombo and Delmastro 2004, Ortega 2009, BenNer, Kong and Lluis 2010
H5
Rao 1971, Lafontaine 1992, Nagar 2002, Foss and Laursen 2005, Devaro and
Kurtulos 2010, Ben-Ner, Kong and Lluis 2010
2011 North American Summer Meeting of the Econometric Society
Description of the Database
Data taken from a survey containing information on the human resources practices and
work organization policies for blue collar workers in Spanish industrial stablishments
Survey designed by a group researchers of the UAB, UIB, UPN and UZ.
Carried out by a specialised company through out personal interviews with plants
directors or operations or human resources managers
Similar to other surveys in the related literature (F&L 2005, Ortega 2009, D&K 2010,
Ben-Ner et al. 2010)
Population comprises the Spanish plants with more than 50 employees and included
in one of the 13 manufacturers sectors of the CNAE clasification
Target group was 3000 companies listed in Comerdata
Response rate of 13.5% (403 companies – stratified sample guaranteeing stratums
by size, industrial sector and regions )
358 observations
2011 North American Summer Meeting of the Econometric Society
Variables
Pay-for-performance strength (p)
The results of the evaluation
performance are linked to
incentives or used to take
decisions about salaries…
Total
disagreement
Disagreement
1
2
Neither
agreement
nor
disagreement
3
Agreement
Total
agreement
4
Distribution: 16.48, 11.45, 18.72, 48.88 and 4.47
4-categories ordinal variable Pay-for-performance (p)
2011 North American Summer Meeting of the Econometric Society
5
Variables
Autonomy (a)
The autonomy of the worker to decide
the implementation (when, how, and in
which order) of her tasks is…
Nil or
very low
Low
Average
High
Very
high
1
2
3
4
5
Distribution: 15.08, 24.02, 53.63, 6.70 and .56
Dichotomous variable Autonomy (a)
2011 North American Summer Meeting of the Econometric Society
Variables
Uncertainty (u)
Qualify the demand of the plant in relation with the following aspect :
Its variability from year to year
Very low
Low
Average
High
Very high
NS/NR
1
2
3
4
5
9
Distribution: 1.96, 12.57, 57.26, 24.02 and 4.19
Three dummy variables: Low uncertainty,
Middle uncertainty and High uncertainty
2011 North American Summer Meeting of the Econometric Society
Variables
Job Complexity
A large number of products
are made in your plant.
The products made in the
plant are very different among
them.
The mix of products made in
the plant can be easily
changed.
Many new products are
introduced every year
The new products are usually
very different of the existing
ones
The products we produce
suffer continuous
modifications
Agreement
Total
agreement
3
4
5
2
3
4
5
5
4
3
2
1
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
Total
disagreement
Disagreement
1
2
1
Neither
agreement
nor
disagreement
Principal component factor analysis (α = .75)
2011 North American Summer Meeting of the Econometric Society
Econometric Approach
H1
H2
H3
J
p  1ui   2 jci   3 ai    j x ji   1,i
*
i
[1]
j 1
H5
H4
J
ai*  1ui   2 jci    j x ji   2,i
[2]
j 1
Identification problems
Model 1 assumes
Model 2 assumes
Model 3 assumes
  1   2  3  0
  3  0
j 0
and
and estimate Equation [1] trough an ordered probit
and estimate Equation [1] through an ordered probit and Equation
[2] through a probit model
j  0
for those variables that were not significant in the former
models and estimate jointly Equations [1] and [2] by a
semi-ordered bivariate probit model (Greene & Hensher
2009)
2011 North American Summer Meeting of the Econometric Society
Table 4
Results of the Ordered Probit and Probit Probability Models Estimations
Model 1
Model 2
Dependent variable:
Independent Variables
p
Dependent variable:
Estimates
p-values
.083
-.21
.236
.35*
.100
.03
.887
.13
.515
.41*
.094
Job complexity
.14**
.039
.18***
.006
.17**
.023
Collective agreements
-.24*
.094
-.47***
.001
-.89***
.000
Unions influence
-.01
.932
-.07
.627
.20
.195
Market Competition
-.13
.349
-.12
.376
-.02
.891
-.29**
.029
-.31**
.020
-.13
.405
Middle Qualification requirements
.22
.192
.39**
.018
.68***
.000
High Qualification requirements
.31
.154
.35
.101
.23
.350
.84***
.000
.95***
.000
.58***
.001
.06
.530
.01
.911
-.14
.165
-.008
.953
.05
.688
.24
.132
.05
.729
.07
.653
.08
.636
Cons
-
-
-
-
.27
.601
Chi2
128.52***
.000
93.02***
.000
93.94***
.000
High Uncertainty
Job stability
Soft skill requirements
Size
Multi-plant
Technological intensity
Pseudo R2
.87***
.000
-.32*
a
p-values
Middle Uncertainty
p-values
Dependent variable:
Estimates
Autonomy
Estimates
p
.15
N
Log likelihood
.11
.19
358
358
358
-363.24
-380.99
-192.61
*Statistically significant at the 10% level, ** at the 5% level, *** at the 1% level
Note: Model 1 is estimated by an ordered probit probabilistic model while in model 2 the Pay-for-performance strength equation is estimated by an ordered probit probabilistic model and
the Autonomy equation by probit probabilistic model.
2011 North American Summer Meeting of the Econometric Society
Table 5
Results of the Semi-Ordered Probit Model Estimations
Model 3
Dependent variable:
Independent Variables
p
Dependent variable:
Estimates
p-values
1.47***
.000
-.38**
.042
.40*
High uncertainty
-.06
.774
Job complexity
.10
Collective agreements
Autonomy
Middle uncertainty
Job stability
Estimates
p
p-values
Dependent variable:
Estimates
a
p-values
.000
.056
-.39*
.030
.40
.062
.49**
.045
-.06
.748
.45
.057
.179
.18**
.018
.22***
.002
.001
.997
-.91***
.000
-.91***
.000
-.28**
.031
High Qualification requirements
Chi2
N
Log likelihood
Rho
p-values
Model 4
Dependent variable:
1.69***
Middle Qualification requirements
Soft skill requirements
Estimates
a
.73***
.000
117.55***
358
-560.32
-.39*
.000
.23
.23
.07
.687
-.26**
.031
.74***
.000
.72***
.000
.33
.169
.34
.135
.53***
.002
.53***
.002
.64***
.001
138.08***
358
-561.26
-.53***
.000
.039
*Statistically significant at the 10% level, ** at the 5% level, *** at the 1% level
2011 North American Summer Meeting of the Econometric Society
.039
Conclusions
 Effort to disentangle the effects of two different informational contexts,
uncertainty and local private knowledge, on the blue collar workers’ pay-forperformance strength and autonomy granting firm decisions.
 Consistent with previous empirical literature, we found that pay-forperformance and autonomy are interrelated decisions.
 We also found that autonomy is positively correlated to job complexity and
uncertainty.
 When we control for autonomy the positive relationship between pay-forperformance and job complexity vanishes and the relationship between payfor-performance and uncertainty becomes negative.
 This empirical evidence provides support for Prendergast (2002) and
Holmstrom (1979) and Holmstrom and Milgrom (1987, 1991).
 We also provide support for alternative explanations (Nagar 2002 – Core
and Quian 2002).
2011 North American Summer Meeting of the Econometric Society