A System Dynamics Investigation of Employment and
Production in the Fars Province Agricultural Sector
Moosavihaghighi Mot Shack
Assistant Professor in “Fars Research Centre for Agriculture and Natural Resources’
PhD in Agricultural Economics,
P.O. Box 71555-617 Shiraz, Iran,
H/P: 0098-9173102356, Fax: 0098-711-7205107
Email: musavee@gmail.com
Abstract
This research analyzes agricultural employment and production in Fars Province while rural
areas are taken into consideration. The researcher will face with some employment problems in
rural areas as a separate problem from static viewpoint. On one hand, employment in rural
areas may relate to labour supply and demand and on the other hand to the social challenges
such as population growth rate and emigration in a systematic model. This study aims at
considering the most measurable issues related to the agricultural employment and production
along with econometrics estimations in the form of a formulated System Dynamics (SD) model.
The overall results indicates that the unemployment problems rooted in rural areas will be
aroused in the urban areas in near future and agricultural production, per capita income, labour
demand and finally employment can be affected by increasing investment in the agricultural
sector. Also, the effective policy in increasing employment is cultivated lands which are increased
by development modern irrigation systems and improvement in agricultural production
technology.
Keywords: System D' ics, Rural Employ Agricultural Production, y Problems,
Agricultural Sector, Rural Emigration, Fars Province,
JEL Classification: JO8, J21, J23, J64, Q13, Q18
Introduction
Over 80 percent of Fars Province (located in Iran country) agricultural activities are centralized
in rural areas (comparative results of agricultural general census, Various Issues). In this respect,
the rural employment should be a symbol of the employment in the agricultural sector in Fars
province. Agricultural sector is risky and uncertain in comparison with the other economic
sectors which affect income, emigration and even life of the farmers. All reforming plans in the
agricultural sector have some weakness and strength points. In total, we cannot perform any
policy without direct and indirect cost. For example, if the policy makers aim that reducing the
production cost and increasing efficiency and exporting ability, they should use mechanization
1
in the sector more than ever. This issue not only cannot solve the unemployment and
emigration problems but also it will intensify them. Thus, increasing employment and efficiency
in the agricultural sector are among the main purposes of the country of Iran which are in
contradiction. At last, the villages as centers of agricultural products and the farmers as one of
the effective factors in the economic development will be more focused.
Villagers’ emigration to the cities with the purpose of finding job, earning appropriate income
and using urban facilities is an increasing and permanent phenomenon in Fars Province. Many
officials and planners think about these issues in this sector. Thirty-year population statistics in
Fars Province reveals that the emigration procedure is increased over time. On the other hand,
job applicants entered the cities could not be employed in industrial sector (based on Major
Industrial statistics in the country, Various Issues) and some of them are employed in other
economic sectors and unfortunately the rest are unemployed. By taking into consideration the
“labor surplus problem” (Fei and Gustav, 1964; Gustav, 2004) in the agricultural sector of Fars
Province and based on the high fertility rate, particularly in rural societies of Fars Province, the
labor supply and employment in the rural areas are significantly deserved to be paid attention.
Thus, when unemployment increases the economics system will lose a considerable amount of
its actual ability as a result of unused capacity of a major factor of production (unemployed
worker).
In these cases, social and economic issues would be analyzed systematically and multilaterally.
Therefore, it can be cited that one of the goals of SD Models is practical and scientific decision-
marking before performing proposed policies. To this end, this research mainly aims at studying
the employment challenges in rural areas of Fars Province in the form of a SD Model by focusing
on socio-economic issues for solving the unemployment problem.
Review of related literature
Al-Jalaly (1992), in his study, “Agricultural sector employment and need for off-farm
employment in Pakistan”, found that the employment could not increase over time in the
agricultural sector. Hence, the government should increase employment in other sectors to
solve unemployment crisis.
Asali (1992) tried to identify the trend and function of the interaction effects of the principal
variable in the Iranian agricultural system. The first section of this paper composed of a model
containing three parts; demand, supply, and marketing. The main reason to make a model was
to understand the interaction to offer controlling suitable polices and directing the system of
agriculture in the country to a desired point. The economic variables, which were influential on
the whole agricultural products’ demands, were simulated on the basis of economic theoretical
context. Using the target model, the result of continuing the contemporary situation, as well as
the effect of the different modification polices were discussed.
Goldsmith and Dissart (1998) simulated their model based on a computerized analytical model
with different scenarios due to privatization and mechanized cultivation during recent years and
examined the role of industry sector in improving the agricultural researches.
Motaghi (1998) took account the employment demand in the agricultural, mine and industry,
gas and oil services sectors in Iran from 1971 to 2006. He paid attention to this issue that long
2
term labor demand played very important role in micro policy making in the labor market since
it was not elastic during long term. Thus, wages in labor market are resulted from the balance
between labor demand and the form of supply function. So, in labor market, demand is
considered as the main factor and determines the price. This study examined the process of
labor demand modifications in different sectors of economics. After determining and providing
the mentioned model, the labor demand was simulated as a part of course of 1996-2006.
Kiresure et al. (2000) analyzed various factors/components/variables contributing to the future
of oilseeds situation in India using the SD methods. The simulated scenario forecasted the
demand for 15 million tones of edible oils. The model was developed and could be successfully
used for a strategic planning, as the simulated data gave a close resemblance with the existing
system. The model could also be used to test various policy options and their reaction in a
complex system like oilseeds. The simulation results indicate that, with proper polices, the
oilseed sector has the potential to meet the domestic demand in the coming decade.
Methodology
In systematic models the boundaries of the model should be specified in order to focus on the
problem statement and objective of study. Dealing with details in systematic models keeps
away the researcher from macro systems as the main purpose of this study is the consideration
of the rural employment in the agricultural sector. Thus, emigration and its effect on the
population and rural labor supply should be taken into account. This study attempted to divide
the model into two parts and analyzed each part in the form of systematic model for audience s'
better understanding and simplicity. Hence, the whole model is presented in economic and
social sectors in this study.
- Economic Sub-model
In the first stage, two functions are estimated for specifying the relationships among main
variables. In the next step, coefficients will be placed in the economic part of SD Model. Here
two functions will be defined as the followings:
By estimating the production function, the coefficients of the relationship between production
and its effective production factors will be determined. Production function indicates a process
in which inputs will be changed to output through a process with a specified technology. Totally,
production function provides a physical relationship between inputs and output.
Cobb-Douglas production function is a common and simple form of a production function.
Q=AK*LEN'T#
In this relation, T, N, L, K, Q, A are respectively considered as time (technological changes), land,
labour, capital, agricultural production and intercept. By obtaining natural logarithm from both
side, nonlinear will be changed to a linear form for estimation.
Wage index in the rural areas is one of the major variables that is required to be estimated. The
results of estimation are used in determining wages levels in the SD model. Net change in rural
wage (NCR), as dependent variable, is considered as function of price index (Indexinf) and
3
minimum supply and demand (RSRES). The RSRES calculated by “rural supply” (RS) is divided
RS
min( RS, EM)
NCR= C +a, Indexinf + a, RSRES
RS
min( RS, EM)
into minimum RS or employment (EM). The mathematical formulations come as follows:
NCR= C +a, Indexinf + a,
Where RSRES=
The estimated coefficients are entered the model. Figure No. 1 indicates the relationship
between production and investment. Agricultural labour along with related coefficient resulting
from econometric estimation, are entered total production. This coefficient was based on figure
-0.522 which indicated that marginal product of Labour (MPL) in this factor of Fars Province
agricultural sector was negative. Other researchers confirmed the negative or zero of the MPL
based on the labor surplus problem in the agricultural sector of Iran (Kahbazan and Gray, 1993;
Khalilian and Yari, 2001; Akbari and Ranjkesh, 2003; Moosavi et al., 2008). In this study, it is
supposed that time can affect the production by technological modifications or production
methods change.
time table time coeficient
capital output
ratio
capital coefficient
capital
scotck
i employment
expected
capital stock ~j—___ production
expected growth labor
rate coefficient
land coefficient > jays
Figure 1: Influence diagram for production and investment in Fars Province Agricultural Sector
The “total production” affects “expected capital stock”. “Expected capital stock” is affected by
“expected growth rate” and “capital output ratio”. “Expected capital stock” influences the
“capital stock” by a delay and the “capital stock” affects production by a feedback loop
mechanism.
Labour supply. excess supply
fornural labor
loymen
demand for. —— = SmPoyme
tural labor price index
Rural wage—— coefficient
_.
real rural wage
price index excess supply
coefficient
Figure 2: Influence diagram for rural wages determination in Fars Province Agricultural Sector
The estimated relationships of wages will be entered the Figure No. 2. Rural labor supply is one
of the main variables of economic model relates to the social model by the rural population. In
other words, “rural population” and “rural labor supply coefficient” will form this variable. As it
is seen in the Figure, employment is determined by supply and demand. Demand for labor is
one of the variables forms by employer of the agricultural sector. Thus, he/she employs labor
based on the productions of the previous years and prediction of the current year. In the
present model, since there is no “money illusion” for employer, so real wage index affects labor
demand and then forms it.
There are three states in labor supply and demand market. Supply and demand are equal
(nonexistence of excess supply or demand in the market), demand is more than supply (excess
demand), and supply is more than demand (excess supply). Rural employment variable is
defined based on the minimum RS or EM and then “excess supply for rural labor” is determined.
- Social Sub-model
Villagers’ emigration is one of the major problems of the country of Iran, especially in Fars
Province. This phenomenon deprives the rural areas of the most efficient labour forces on one
hand and increases the urban unemployed rate and consequently brings about social-economic
dilemmas. Emigration from rural areas to the urban areas is considered as a desirable fact in the
economic development texts from the past decades. It was assumed that internal emigration is
a natural and pleasant process in which extra labors exists from the rural areas gradually move
in order to provide the required labor for urban industry growth. The main assumption of this
process is that the human resources are transferred from places with zero “social marginal
productivity” to the ones with positive “social marginal productivity” and it will be grown as a
result of high capital density and technology development. In fact, this process causes
productivity increase in the agricultural sector. In contrast, emigration procedure from rural to
urban areas exceeds the capacity of urban appropriate occupations and even providing urban
job opportunity capacity cannot meet it. Thus, it seems that the desirability or undesirability of
the villagers’ emigration to the cities is a relative issue and it is completely different due to the
time, place and environmental factors situations.
Michel Todarow and Smith (2003) state that emigration motivation is basically intellectual
consideration of profit and relative transferred cost, although it relates to finance and may be a
mental one. The previous studies on the emigration in Fars Province indicate that lack of the job
5
opportunities and differences income in these areas (rural and urban) are the main causes of
the villagers’ emigration. In the present study, these two factors are considered as the main
reasons of the emigration in the model.
Emigration in this study is important since its effect on the rural population and employment is
significant. Basically, there is a significant mutual relationship between rural emigration,
employment and unemployment. Rural population is decreased by increasing the number of
emigrants and then rural labor supply will be affected and the unemployment in villages would
be decreased.
nal abi
bee a supply Rate of Increase in Ret of boas in
Sw ural life industrial Sector job construction and service
expantancy sector job
rural birth rate
constant
aval = «i =« oS 5 eee
7 Raté of increase in job
opportiunties in Urban
Area
unemployment rate
‘ral bith rate rural death rate
Net ratio defences in
rural and urban area
Average Wages in wages Probability of finding a
erage Wage
ural Area job in wban area
Average Wages in
Urban Area Defrence in lving cost
inthe area
Figure 3: Influence diagram for the rural population and emigration in Fars Province
In Figure No. 3, job opportunities in rural areas are seriously limited since rural population is
growing in Fars Province. Job opportunities are one of the factors which motivate the villagers
to emigrate to the cities and it is directly related to the “probability of finding job in urban
areas”. These opportunities are existed in services, construction and industry sectors.
“Net ratio difference in rural and urban areas wages” is one of the effective factors on the
decision making of emigration. Lack of “job opportunities” and “difference in average wages in
urban and rural areas” in the present model causes the rural labours’ emigration due to a logical
delay in decision making. Although, the wages differences are important, the main point is that
rural and urban living levels should be considered in decision making of the villagers. For
instance, the considerable part of difference in wages should be considered for living cost in the
cities such as rental fee, commuting from villages to the cities, replacing initial charge, improper
access to the rural agricultural products (self-consumption) and other unpredicted and luxurious
charges in the cities. Thus, “net ratio differences in ....” is affected by difference in living cost in
urban area. In the last stage, “rate of increase in job opportunities...” , “net ratio difference in
rural and urban areas wages” and “unemployment rate” are effective factors in forming
emigration by logical delay. Finally, emigration mutually affects rural population and vice versa
by feedback loop mechanism.
Rural population in the social model would form the labor supply in the economic model.
Difference in rural labor supply and employment specifies the unemployment, and affects the
emigration level. In other words, the more increase in unemployment rate in a period of time
the better positive effect on emigration rate in the social model. These two feedbacks are
performed in the social and economic models.
Results and Discussion
The simulated agricultural products are indicated in Figure No. 4. Production value was
approximately fixed at the beginning of the years 1990 to 1993 and oscillated from 1995 to
2002. Provided that the trend is smoothed during the mentioned years, there will be no more
considerable changes. The production had a descending trend by fixing other conditions and
production techniques from 2003 to 2025. This process will be put into practice due different
reasons including underground water resources decrease’, a high labors/land ratio, traditional
production methods, etc.
Agricultural production
1990 1995 «2000 ~=«i0HCSCNSCiSSCSSCS
‘Time (Year)
production : Socio-economie______________— RiaYear
Figure 4: Simulated Production in the Fars Province Agricultural Sector
Labor demand is presented in Figure No. 5 and it is originated by the employer in the
agricultural sector. Thus, it would be affected seriously by the production oscillations and real
wages level. The demand between the years 1990 to 2010 had large oscillations during a 20-
year period in the form of a dampened oscillatory. Then, it will have a fixed trend during the rest
fifteen-year period from 2011 to 2025. Such a behavior is seen in goal seeking systems.
Agricultural Demand
sono
\
ssa
1
| \
coon |A\ | NaN TAY oc ———
2sno
200,000
79% 2000-2005 ~—=—«NI=«C«NSS«CODDSCS
Time (Year)
demand for rural labor : Socio-economie Person
Figure 5: Simulated Labour Demand in the Fars Province Agricultural Sector
+ In Fars Province, underground water resources provide over 80 percent of the agricultural water usage.
7
It can be concluded in this Figure that the agricultural demand for rural labors will not be
increased during the next years and the agricultural sector not only cannot solve the
unemployment problem in the future but also it will spread it in the cities based on the
increasing emigration rates and intensifying unemployment in cities suburbs.
Rural labor supply is increased by a decreasing rate, during the years 1990 to 2005 and it will be
reduced from 2006 to 2025 as a result of villagers increasing emigration rate to the cities after a
maximum point in 2005. There is 7 to 18 percent difference between simulated rural labor
supply and actual data between the years 1996 to 2006 (based on Housing and Population of
General Census, Various Issues), however their trends are the same. Based on simulated data in
2007, labor supply is less than 300000 and it will be reached to 260000 in 2012.
Supply for Labour
1990 1995 2000 ~—«2005—=—«MNS~=CNS «C20 —«S
Time (Year)
rural labor supply : Socio-economie————______— Person
Figure 6: Simulated Labor Supply in the Fars Province Agricultural Sector
Excess Labor supply is demonstrated in Figure No. 7 as excess supply for rural labor. In case that
this variable is less than one, it will be excess demand and if it is more than one, it will be excess
supply.
Excess Supply for Rural Labour
cael ww —— |
sso) 1995 2000 ~—«2005-~=«SCiSSSC SSCS
Time (Year)
‘exoess supply for rural labor: Socio-economie mal
Figure 7: Simulated Excess Labor Supply in the Fars Province Agricultural Sector
As it is seen, this Figure is an oscillating and descending trend after 2011 in a way that the small
excess demand will be later revealed because of increasing emigrations. The supply and demand
would be structurally modified due to different reasons and the demand would exceed supply
of rural labor. This is to say that if the system takes no action and unemployment problems in
cities are ignored, the unemployment problem in villages will be solved as a result of several
reasons including high emigration rate and even during next 14 years there will be a little excess
demand for labor.
Figure No. 8 shows the rural unemployment level. This variable has serious oscillation with
dampened oscillatory between the years 1990 to 2010. The difference between peak and
unpeak points is 60000 persons. Some of these oscillations may relate to the randomness in
agricultural production and they will have several cycles during different years.
unemployment level
i Wh \ A
0
1990 1995 2000 2005 —«al0~—=«abls ~—=«m0a0~=—=«S
Time (Year)
Figure 8: Simulated Rural U ploy in the Fars Province Agricultural Sector
These dampened oscillations have been finished since 2010 and the Figure will be completely
decreased. This decrease is resulted from rural population reduction due to emigration rates
during past years, rural labor supply decrease and increase in labor demand.
Right now different scenarios are taken into consideration in relation with progressing
important variables. Each scenario will be performed based on a specified policy or combination
of policies.
- Scenario 1: Considering the Effect of Progressing in “Capital Output Ratio”
In this scenario it is supposed that capital output ratio may be improved for two percent yearly
by applying new technology in the agricultural sector and using a series of plans like ground
laser leveling, using new machineries in cultivating and harvesting procedures. This policy would
be continued from 2010 up to the end of simulation course. Figure No. 9 shows the effect of this
policy on the agricultural production.
production
600
500
400
300
200
19901995 2000S 2005S 2010015) 2020» 2028
Time (Year)
production : Capital Output Ratio Inc: Rial/Year
production : Soc Rial/Year
Figure 9: Scenario one, “Improvement in Capital Output Ration” and its Effect on Production
in Fars Province Agricultural Sector
The effect of this policy on production is significant and it will stop the production descending
process. But it has less effect on demand and employment. Therefore, it is considered as
production increase policy, while, its effects on other variables such as emigration, population,
unemployment etc. is not observed.
- Scenario 2: Considering the Effect of Increasing Investment Annually, 2.5 Percent yearly
Figure No. 10 and No. 11 reveal the effect of this policy on production and employment. It is
supposed that the government would increase the present investment rate for 2.5 percent each
year from 2010 up to the end of simulation course by granting capital to the agricultural sector
continuously. The government would invest annually by a reforming polices. In a way that its
credit is provided (by low interest rate loan or gratuitous loan) and the capital will be
continuously raised in the agricultural sector. It is required to mention that performing this
policy and providing financial support are difficult for the government since the governmental
financial resources will be under pressure. As it is seen, the effect of this policy on the
agricultural sector is significant and has no much effect on the employment.
production
600
500
400
eee
200
199 199520002005. 010205 20202025
Time (Year)
production : Capital Rial/Year
production : Rial/Year
Figure 10: Scenario Two, "The Effect of Increasing Investment" and its Influence on the
Production in Fars province Agricultural Sector
employment
400,000
350,000
mh NN AK p=
250,000
200,000
1990 199520002005 20102015 20202025
Time (Year)
employment : C Person
employment Person,
Figure 11: Scenario Two, "The Effect of Increasing at" and its Infl e on the
Employment in Fars Province Agricultural Sector
10
- Scenario 3: Equality in Wage Rate in Rural and Urban Areas
As other conditions are unchanged (no change in other parameters and constants of the model)
the model is simulated based on this scenario and its results as the scenario (policy) No. 3 for
rural population and unemployment are presented in Figure No. 12 and 13. In this case the
government would nullify the difference in rural and urban area wages during 15 years. For
instance, this policy can be applied in the agricultural sector by increasing rural emigration
expenses or continuous increase in agricultural wages. As it is seen, the application of these
policies would have unpleasant effect on unemployment level in the rural areas.
Rural Population
1990 19952000 -«2005.=S 201020152020» «2025
Time (Year)
Rural Population : Equality in wag
Rural Population : Socio-economi
Person
Person
Figure 12: Scenario Three, "The Rural and Urban Wages Equality" and its Effect on Rural
Population of Fars Province Agricultural Sector
unemployment level
0
1990-1995 ——«2000=—«2005-—SsO1DSsNSSHMSCS
Time (Year)
level : Equality in
Figure 13: Scenario Three, "The Rural and Urban Wages Equality" and its Effect on Rural
Unemployment of Fars Province Agricultural Sector
- Scenario 4: The Differences in Rural and Urban Area Wages are Doubled
This scenario is shown in Figure No. 14 and its main effect will be on emigration and increases it
from 2010 to 2025. Also it would influence rural population, labor supply and employment in
the agricultural sector. As it is cited before, the unemployment rate in cities is seriously
increased and causes other problems.
11
Net flow of Immigration
4,000
35,000
30,000
25,000
20,000
19901995 «2000 2005-=SNSCOSSOMDSSCOS
Time (Year)
Net flow of Immigration : Inequality in wages ———— Person/Year
Net flow of Immigration : Socio-economie— Person/Year
Figure 14: Scenario Four, "Increasing Inequality of Rural and Urban Area Wages" and its Effect
on Rural Net Emigration of Fars Province Agricultural Sector
Other scenarios such as consideration of the effects of under cultivated lands increase due to
irrigation systems improvement’, combination of scenarios No. 1 and No. 2 (2.5 percent growth
in annual investment along with technological changes), job opportunities and the probability of
finding jobs in cities (increase/decrease) are taken into account and analyzed and their overall
results will be presented in conclusion.
Conclusion and Suggestions
This study simulates the future prospects of labor status and production based on SD socio-
economic model in Fars Province Agricultural Sector. To this end, chronological trend of other
important variables (population, emigration, unemployment, labor supply and demand etc.) is
simulated. Afterward, the following conclusions are reached by performing the reforming
scenarios (policies) and their comparison with current trend of the system (system without
reforming policy).
1- Due to the villagers’ emigrations to the cities the rural population is continuously
decreased and the percentage of urban population in compare to the rural population is
significantly increased. Thus, the unemployment is rooted out from rural areas and is
gradually extending to cities. In contrast, unemployment problem in rural areas is not
important in near future.
2
In case of executing the policy of “equality wages in rural and urban areas”, “decreasing
the probability of finding jobs in urban areas” and providing the “job opportunities in
rural areas”, the emigration will be controlled in a long term period to some extent. Of
course, performing the effect of policies of rural incomes improvement would be more
successful than rural job opportunities. In contrast, when “difference in rural and urban
area wages” are increased based on governmental policies or structural changes, the
7 It is supposed that under cultivated lands in Fars Province are annually increased about 10000 hectares. This
policy will be continued for a period of ten years from 2012 to 2021 after that stopped. Also it can be performed in
different ways (like Laser Land Leveling, constructing dams, Conservation Tillage, Canal water Supply System,
Convey Canal, Implementation Ground Water Recharge Pound, Drought Resistance Varity and Compatible Species
with Dry Land) and leads to cultivate the fertilized lands confronted with water shortage in the past.
12
-
a
rural emigration and population will be seriously affected and consequently, the rural
population will be decreased.
Emigration to the cities will be certainly reduced by performing the policies of rural
incomes improvement and balancing income and facilities between rural and urban
areas. In this case, rural population is increased and the policy makers should consider
some systematic plans for decreasing unemployment in rural areas.
As the capital has a positive marginal product (MPK>0)°. Investment in agricultural sector
may be an efficient policy in increasing production in SD model. This policy can influence
total production in the agricultural sector, per capita income, total capital, labor supply
and demand and employment by increasing investment suddenly in a short term period
or investment rate continuously increase in long term period.
The under cultivated lands in Fars Province can be increased by improving irrigation
systems and changing production technology and it will affect better the employment
increase (because of fertilized under cultivated lands faced serious water shortage) in
compared with other policies.
Performing the country’s macro policies in controlling inflation rate and wages has no
considerable effect on production and employment in agricultural sector in a short term
period. And they will be effective in preventing the spread of unemployment in rural
areas when this policy can be used as a complementary one along with other policies.
Other suggested policies may be presented and examined by policy makers. Since the
policy makers have more precise information of the executive system abilities and they
can better do “policy evaluation”*. In addition, policies in short term and long term
periods have different effects and should be taken into consideration.
Finally, it is required to mention that there is reverse relationship between simulation
period and the validity for policies effects as structural changes may be occurred in long
term periods. This is to say that, the more simulation period the less care in commenting
suggested policies.
Each research can respond limited questions and provide the new ones more than the
responded questions. This is one of the research specifications, particularly the social-economic
researchers. Therefore, there is no claim that Fars Province rural unemployment problems are
solved
and all social and economic issues are considered in this study. This model only will help
the policy makers and planners in practical and scientific decision making.
® Marginal product of capital (MPK) is equal to 0.659
* Refer to situation in which a decision maker must choose one policy, called “plan”, from a given set of alternative
policies.
13
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14
Appendices
Appendix A- Flow Diagram for the Socio-Economic System Dynamics Model
in Fars Province Agricultural Sector
(Model Structure)
fae rue bith ete
constant
Eetecmebrnt Rate of Increase in
arena industrial Sector job Rate of increase in
dekay constuction and sevice
\ \ ra job
lcent |
capital output |
ratio "Rai ofinrease in ra
—— | i
( | i peel cpus Ui
expected . 4 |
capital stock q—__ production
1 N : code
\ f sy a
expected gow Netfow of
rate : > Inmigration
4 unemployment Probabiiy. ra
job inwban area |
Delay njob
production delay opportuns
one | Average Wagesin Netra defences in PD
/ ’ aa care i Rural Area nl a etis
ve y mice index
delay into alnalwae spect E 1
production \ Delay in wage
| defence
|
production delay |
a | 1 Average Wages in Defrence in living cost
ral ege ntl ap tyne lg
i
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Appendix B- Econometrics Estimations Results
Cobb-Douglass production function estimation results by taking time factor into consideration is
presented as follows:
LnQ, =-0.522LnL , + 0.659LnK , +1.307N , +3.56*10-10LnT,
(-10,394) (5.707) (12.709) (2.604)
R2=0.3 , R2=0.93
D.W.Stat.=2.23 , F-Stat.=129.715
Respectively, T,Q,N,K,L are time, total production, under cultivated lands level, capital and labor
in the agricultural sector. T-statistics are presented in the parenthesis and these estimation
results indicate that all estimated coefficients in 0.99 levels are significant. The model will
structurally have no autocorrelation, multicollinearity and heteroskedasticity problem.
Estimated Durbin-Watson (DW) statistics checked with relevant statistics in the table and placed
in the area that autocorrelation hypothesis is rejected. F statistics is acceptable in 99% level .As
it is seen, this regression is increasing return to scale. Time affects production positively but
effect is so small. Unfortunately, it reveals that technological changes happen through a weak
trend in the past years.
In the next estimation net change in rural wage (NCR) a function of inflation rate (indexinf) and
excess labor supply (RSRES) is considered. Here, as it is expected the inflation rate and labor
supply would respectively have positive and negative effects on wage rate.
NCR =19.75775 + 0.488028 * Indexinf - 16.46264 * RSRES
(14.79) (3.030) (-2.93)
where RSRES = __ BS.
Min(RS, EM)
All coefficients in 99 percent level are significant. Adjusted R? is equal to 0.995 placed in a
suitable level; DW statistics indicates the nonexistence of positive and negative autocorrelation
problem. Although, time series data is used but DW equal to 1.97 which is near to figure 2. EM
and RS respectively show employment and labor supply.
If RS >EM -—> RSRES T then» NCR JV
If RS <EM -—>RSRES J then—> NCR T
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