Is It a way Out of Crises for White Meat Producers to Focus On Export Strategies During Crisis Times?


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Is-It-A-Way-Out-of-Crises-for-White-Meat-Producers 2011 Procedia---Social-an

3. Data and Methodology 
Data: The data for this study includes the export and production quantity data of the chicken meat 
industry in Turkey from 1981 to 2010. The data was gathered from the Food and Agriculture 
Organization of the United Nations (FAO). Annual production and export data is illustrated in Figures 1 
and 2. These figures exhibit the typical exponential increase with time. The important point that Figure 2 
illustrates is the existence of breakpoints for the years of 1994, 2001 and 2005. It is known that in 1994 
and 2001, Turkey was faced with important economic crises, which affected almost all production 
sectors. In addition, the 2005 crisis was a sector specific crisis affecting the chicken meat sector, because 
of the Avian Influenza. In this paper, we attempt to fit an appropriate curve to the data by using a 
polynomial structure of a time trend and dummy variables that represent the crises. 
Figure 1: Chicken Meat Production (Ton/Year) 


Cüneyt Akar et al. / Procedia Social and Behavioral Sciences 24 (2011) 300–307
303
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
CHICKEN MEAT PRODUCTION
Figure 2: Chicken Meat Export Data for Turkey(Ton/year) 
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
82
84
86
88
90
92
94
96
98
00
02
04
06
08
10
CHICKEN MEAT PRODUCTION
Curve Fitting: Curve fitting is the process of constructing a curve that fits the data best. There are 
different ways of curve fitting, classified as parametric and non- parametric techniques. In this study, we 
use the parametric curve fitting techniques, namely polynomial regressions (polynomial curve fitting). 
The curve fitting equation can be written as follows:
0
1
94
2
2001
3
2005
1
(
)
T
i
t
i
t
i
EXP
TREND
D
D
D
β
β
δ
δ
δ
ε
=
=
+
+
+
+
+
¦
(1) 


304
Cüneyt Akar et al. / Procedia Social and Behavioral Sciences 24 (2011) 300–307
Where: 
t
EXP
is the chicken meat export quantity measured in tons and 
TREND
is a linear time trend 
which takes on the values of 0, 1, 2, T. 
94
2001
2005
,
,
D
D
D
are dummy variables which represent the 1994, 
2001 and 2005 crises, respectively. The definition of dummy variables is presented in Table 1. 
t
ε
is the 
error term, which follows a normal distribution with a zero mean and constant variance. In Equation (1), 
the model is linear with respect to the coefficients. In order to estimate Equation (1), we use the least 
squares method; the order of is selected as the trial and error method for the best fit. 


Cüneyt Akar et al. / Procedia Social and Behavioral Sciences 24 (2011) 300–307
305
Table 1: Definition of Dummy Variables 
Dummy Variable 
Definiton 
94
D
1 for the year 1994 
0 otherwise 
2001
D
1 for the year 2001 
0 otherwise 
2005
D
1 for the year 2005 
0 otherwise 

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