Download Impact of Climate Changes on Economic and Agricultural Value

Khalid, Mahmood and Rukh
Impact of Climate Changes on Economic and
Agricultural Value Added Share in GDP
Ali Awais Khalid, Faisal Mahmood and Gul Rukh
Lahore Business School, The University of Lahore, Lahore, Pakistan
[email protected]
ABSTRACT
The purpose of this study is to investigate the effect of climate changes on
agriculture sector and overall economies. Our main focus is on negative effects of
climate changes on GDP and agricultural value added share in GDP. For the
empirical analysis, we collected data of countries adversely affected by climate
changes from World Bank development indicators over the period 1990-2014.
Our dataset is panel data, so we applied OLS and fixed effects regression
techniques. The statistical results of the fixed effects estimation method support
the view that climate changes negatively affect the GDP of these countries.
However, we did not find support for the effect of climate change on Agriculture
value added share in the GDP. The findings of this study will help the society by
directing them to focus more on climate changes as these changes are affecting
most of the countries. There is a need to respond to these changes for survival of
the developed and developing countries. This is one of the few studies which have
investigated the effect of climate changes on Agriculture value added share in
GDP by considering the most affected countries.
Keywords: Carbon Emissions, Agricultural Value Added GDP Share, GDP.
INTRODUCTION
Global climate temperature has been increasing in recent years because of
greenhouse gases emissions. International climate policy has been focusing on
reduction of climate rise. This is an important element for the developed countries
in the current climate conditions. It has been recognized that developed countries
need to reduce their emissions to 80-90% of 1990 levels till 2050 (Ruamsuke,
Dhakal, & Marpaung, 2015). Depending on the cumulative emissions
accumulated in the atmosphere, the long-term global temperature stabilization
level can be translated into a range of emissions levels by year with different
chances of reaching the 2_Centigrade target in the next century. Why climate
change has been the subject of research in recent years? The reason is that climate
change has a profound effect on economic and social wellbeing of a country.
Economic growth and future welfare is also affected by the climate change. The
horizontal linkages of sectors also prove to be crucial in determining the effects of
climate change (Ciscar et al., 2011; Tol, 2009). For example, due to the effect of
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Khalid, Mahmood and Rukh
climate change on agriculture, the irrigation needs may rise and water supply may
decrease.
One of the dynamic effects of climatic change and economic growth is capital
accumulation. The main dynamic effect is via capital accumulation. If the savings
rate is assumed constant, the amount of investment in an economy will reduce in
case the climate change has a negative influence on the GDP of the country.
These negative consequences of climate change for economies will lower the
availability of investments and capital stock. Consequently, per capita GDP
consumption of agricultural products will also decrease. The shortage of capital
for agricultural and industrial needs due to lower GDP may also have adverse
impact on development in technology and development of human capabilities
through education and training programs. Second, savings behaviour should
change due the significant climate changes as the glaciers are melting down and
heat waves and storm are affecting these economies as glaciers are melting down,.
Hence, to overcome financial problems arising due to future natural calamities,
we need to accumulate the capital for maintaining the future GDP. This increased
saving will be beneficial in future to compensate the losses due to climate
changes. However, these changes in the climate have adverse impact on the
capital productivity as lower returns are offered for investment. The effect of
capital accumulation and savings are studied based on neo-classical growth
theory.
Climate change affects agriculture and food production in complex ways. Due
to climate changes, conditions for agricultural production are changing. As a
result, lower output affects the economic growth and the income of the producers
and consumers. Since, the effect of climate changes depends on the nature of
proxy we will use for climate changes, therefore, the consensus has not been
developed so far. The existing studies, such as Creutzig et al. (2015), suggest that
any change in rainfall and temperature affects the agricultural output and crops
yields. Climate change will also affect the ability of individuals to use food by
altering the conditions for food safety and changing the disease pressure from
water, and food-borne diseases. The frequent heat waves, storms and floods will
negatively affect the food production. However, an increase in temperature will
increase the cultivatable land area that subsequently will increase the food
production.
Schmidhuber and Tubiello (2007) suggested that availability and access to
food items is necessary for wellbeing of world population. This effect is
significant in most of the developing countries in which peasants and small
landowners produce the food on their land. Ito and Kurosaki (2009) explained that
the change in weather reduces the food yield in developing countries. The small
farmers are vulnerable to climate changes, as they do not have necessary capital
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stock to recover losses due to floods, storms and other natural calamities.
The climate change can also affect the agriculture of any country. Mostly, the
agriculture sector of developing countries contributes to a larger part of their
GDP. Hence, it can be anticipated that developing countries will suffer more in
the changing environment. The production of agricultural products is affected by
higher temperatures, heat waves, changing weather patterns and high carbon
dioxide levels in the atmosphere. However, the effect of these factors is positive
in some countries and negative in others.
The production and the quality of cultivated crops and their use of water are
influenced directly by local climate variables and atmospheric Carbon Dioxide
(CO2). Agriculture is particularly susceptible to climate change. Agriculture is the
main user of land and water that plays a dominant economic role in many
countries. However, in the existing literature, no study investigated the role of
climate changes on GDP in the countries those are mostly affected by these
climate change events (floods, storms and heat waves). Hence, this study
contributes in the existing literature by empirically finding the answer to the
following research question that how climate changes impact the GDP and the
Agricultural value added share in the GDP? Our findings support our hypothesis
that climate changes affect the GDP of these countries but we did not find
convincing evidence regarding the effect of climate changes on Agriculture value
added share in the GDP. This may be due to small share of the Agriculture sector
towards GDP. Hence, these findings guide the policy makers to work for
mitigation of these climate changes by signing different environmental protection
agreement with developed countries for restriction of carbon emissions as the
climate changes in future will significantly reduce the GDP of developing
countries.
LITERATURE REVIEW
The existing literature shows the different effects of climate changes on
health, agricultural and economic problems associated with these changes.
Climate changes lead towards economic losses to the most vulnerable countries.
These economic losses include the loss of GDP and the consumption due to
reduced agricultural productivity or damages to infrastructure of these countries
i.e. roads, bridges and other means of transportation of products from agricultural
farms and markets. Mostly, existing studies discussed the role of climate change
in determination of GDP and consumption of products. Second, strand of
literature discussed the consumption and its impact on temperature and
greenhouse gases, for example, increased consumption of electricity and Air
conditioners increase the emission of these gases. Following studies explained
different aspects of this relationship.
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Pindyck (2007) tested the relationship of change in temperature on GDP
growth rate by expecting the long term impact of global warming on future GDP
and consumption. However, other authors criticize future uncertainties associated
with environment, as we cannot predict the future weather patterns. Tol (2013)
was interested in determining the effect of climate change in last two centuries.
Tol found that an increase in temperature has reduced the water resources and
adversely affected the health. The author further reported the negative effect of
these changes for poor countries until 1980s as the effect of climate is positive in
20th century but it turns negative in the 21st century that is associated with
shortage of water as sea level rise, food shortage and biodiversity.
Lo and Chow (2015) investigated the role of climate change on the wealth of
the countries by empirical examination of 33 countries. They reported that 'the
importance of climate change’ is positively associated with per capita GDP but
negatively associated with the risk perception. The perception of these threats
regarding weather changes leads towards provision of resources to decrease the
future risk associated with these events. Ciscar et al. (2011) discussed the physical
and economic effects of climate change in the Europe. They stressed the need for
regional studies for effective policymaking. The author checked the impact of
climate change on floods, agriculture, tourism and coastal areas and human health.
They expect the rise in temperature in Europe that may reduce the 50% welfare
growth of Europe because of losses, but the effect of these changes on agriculture
is positive. The existing literature has also examined the effect of climate change
on different factors including health (McMichael, Woodruff, & Hales, 2006; Patz,
Campbell-Lendrum, Holloway, & Foley, 2005), agriculture and water resources
(Darwin, Tsigas, Lewandrowski, & Raneses, 1995; M. Parry, 1992; M. L. Parry &
Ruttan, 1991; Piao et al., 2010) and economic factors (Ciscar et al., 2011; Eboli,
Parrado, & Roson, 2010; Kane, Reilly, & Tobey, 1992). Unfortunately, the
consensus has not been developed so far. Hence, we will contribute to this stream
of literature by examining the role of climate change in GDP and Agriculture
value added empirically by choose the most vulnerable countries for these climate
changes as this sample is not taken in the existing literature.
RESEARCH DESIGN AND METHODOLOGY
Population and Data Collection
We have collected the data from two sources i.e. World Bank Development
Indicators and Food and Agriculture Organization. Food and Agriculture
organization provides the data about production and consumption of crops,
environment, input prices and macro-economic variables affecting the agriculture
sector. Specifically, we have collected the data of GDP and share of agriculture in
GDP and control variables from the Food and Agriculture organization database.
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Khalid, Mahmood and Rukh
On the other hand, World Bank Development indicators database provides
information about the macro economic variables, investments in financial markets
and financial development in developed and developing countries of the world.
We used this database for extraction of the carbon dioxide emissions in countries
included in our sample.1 From this database, we have filtered the countries mostly
affected by the natural disasters because of climate change. The choice of
countries is based on Global Climate Risk Index Report 2015 by Kreft, Eckstein,
Junghans, Kerestan, and Hagen (2014).2 According to this report, the selected
countries are mostly affected by changes in weather and suffered huge losses
because of climate changes and natural disasters (i.e. heat waves, floods and
storms). The time span of the study is 1990-2013 as in this time natural climate is
affected by carbon dioxide emissions from industries, transportation etc. Our final
dataset includes 239 observations but this data is unbalanced panel data as missing
values are also present in our data as data of some countries and variables is not
available from the secondary data sources used in this study.
Research Methodology
We have used pooled OLS regression, random and fixed effects regressions to
test the relationship of climate change on GDP and Agriculture value added as
share of GDP. First, we applied Pooled OLS regression for checking the impact of
climate changes on GDP and Agriculture value added as share of GDP with some
control variables. However, for panel data, use of OLS regression ignores the
panel data structure and does not provide consistent results. Therefore, we have
also applied fixed and random effects methods first for calculation of Hausman
test and then after selection of fixed or random effects method we applied fixed
effects for explanation of results. Before going further, we will explain the
estimation methodologies. We have unbalanced panel data of different countries
from 1990 to 2013. This time period is enough to observe different changes in the
climate as the carbon emission is rapidly increased with the industrialization in
last two decades. So this dataset includes those times when these emissions are
not higher and the current period of high carbon emissions. Panel data includes
the repeating observations of countries in different times. This data structure is
more useful than time series or cross sectional data as it considers both changes in
cross sectional units (countries) of the study and the time in years. So panel data
tests explain changes due to both cross sectional units and time.
Further, panel dataset provides more consistent and efficient estimates than
OLS. Therefore, we used fixed or random tests to control country specific factors.
We have also used OLS regression. We have unbalanced panel data; therefore,
our focus is on fixed or random effects. We used Hausman test to check if random
effect or a fixed effect is more appropriate for the after observing Hausman test p1
2
Appendix Table 7 shows the list of countries included in our sample.
https://germanwatch.org/en/download/10333.pdf
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value. Hausman test is also used to test whether random effects provide the more
appropriate estimates or the fixed effects model provides consistent outcomes.
This is determined by observing Hausman p-value. If the p-value is less than 0.05
then fixed effects is more appropriate otherwise random effects is applied. These
fixed and random effects have different characteristics such as, random effects
model is in which individual firm specific effects are random and have no
correlation with explanatory variables used in the study. On the other hand, fixed
effects method consider individual firm specific effect with explanatory variables.
Fixed effects model controls the individual effects by assuming that the individual
firms might affect the results and this will exclude the time invariant variables.
We have also applied fixed effects estimation method in this study. The fixed data
is more appropriate for small sample size as our sample size is small and fixed
effect is also suggested by Hausman test.
Research Hypotheses
The hypothesis, no doubt, plays very significant role for designing and
comparing different research techniques empirically as well as theoretically. For
this particular study, hypothesis developed and tested empirically to discuss the
relationship between climate changes and GDP and Agriculture share in GDP.
Our main consideration is on climate changes and we will explain how these
changes impact the Agricultural output and GDP of the countries in the sample.
Carbon dioxide emission is used as indicator of climate changes and more
emissions of these greenhouse gases disturb the natural climate that have
devastating effects on the GDP and these countries suffer losses due to floods,
storms and heat waves (Kreft et al., 2014). Climate changes and global warming
are associated with different factors such as the increase in temperature due to the
higher emission of greenhouse gases is a threat for developed and developing
countries. These climate changes are associated with the rise in temperature and
decrease in rainfall in different countries.
Moreover, these changes in climate are hurting the agriculture sector as
floods, heat waves and storms occurring at regular intervals are destroying the
agricultural crops, cereals and fruits and have adverse impact on livestock. These
countries are suffering huge losses due to floods and storms because of these
changes. The temperature of the world is increased from the last decade that
changes the environmental eco systems while farmers in these countries are using
the traditional cultivation methods. Due to those traditional methods they are
vulnerable to these losses as advanced farming methods are not applied to
increase the output. As a result, the agriculture output is reduced which means
Agriculture share in the GDP is reducing as crops are destroyed by these natural
calamities which later reduce the GDP of these countries.
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H1: We expect the negative influence of climate changes on Agriculture Value
Added (AVAGDP).
H2: We expect the negative impact of climate changes on Gross Domestic
Product (GDP).
Empirical Models
We have developed the following two models for investigation of the effect of
climate changes on GDP and Agriculture value added share in GDP. We have also
controlled the factors such as FDI, Government expenditures, fertilizers use,
capital stock and net production index as these factors influence the dependent
variables but we are not interested in exploring these factors.
Baseline Model (Climate Change and GDP)
(1)
Where; In the above baseline model of equation (1) dependent variables is
LNGDP that is Natural log of Gross Domestic Product (US$, 2005),CO2EM is
main explanatory variable that shows Carbon dioxide emissions (kg per 2005 US$
of GDP), The control variables includes, AFDI that depict FDI inflows to
Agriculture, Forestry and Fishing (Share of total FDI), LNCST is Natural log of
Net Capital Stock (constant 2005 prices), AGEXP show central government
expenditures on agriculture, forestry, fishing (Share of total government
expenditures), AGARE is percentage annual change in agricultural area, ANPI
show Agricultural Net Production Index Number (2004-2006 = 100), LNFCONSP
is the Nitrogen + Phosphate Fertilizers use on permanent and arable crops, µi,t =is
error term and α represents country specific individual fixed effects.
Climate Change and Agriculture Value Added Share in GDP
(2) In the above baseline model of equation (2) dependent variables is AVAGDP is
value Added, agriculture, forestry and fishing (Share of GDP), CO2EM is main
independent variable that shows Carbon dioxide emissions (kg per 2005 US$ of
GDP). The control variables includes, AFDI that depict FDI inflows to
Agriculture, Forestry and Fishing (Share of total FDI), LNCST is Natural log of
Net Capital Stock (constant 2005 prices), AGEXP show central government
expenditures on agriculture, forestry, fishing (Share of total government
expenditures), AGARE is percentage annual change in agricultural area, ANPI
show Agricultural Net Production Index Number (2004-2006 = 100), LNFCONSP
is the Nitrogen + Phosphate Fertilizers use on permanent and arable crops, µi,t =is
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error term and α represents country specific individual fixed effects.
RESULTS AND DISCUSSION
The following tables shows the results of the study for testing of hypothesis
about climate changes and GDP and Agriculture value added share in the GDP.
Table 1 gives summary statistics including mean, median, max, smallest value and
standard deviation of the variables used in this study. The average Agricultural
value added share in the GDP is 0.17 through mean and median is 0.16 that shows
no outliers in the data. The standard deviation is 0.07 that shows the deviation of
values from mean. This variable has 238 observations and maximum share in
GDP is 0.35. The average GDP is 10.86 and its standard deviation shows value
1.68 that shows less deviation from mean.
Table 1: Descriptive Statistics
Variable
Agri Value Added
(Share in GDP)
(AVAGDP)
Natural Log GDP
(Current US$ 2005)
(LNGDP)
CO2 Emissions
(KG per GDP)
(CO2EM)
Agriculture FDI
(AFDI)
Natural Log Capital
Stock (LNCST)
Agri Expenditures
Agricultural Area
(AGARE)
Agri Net
Production Index
Natural Log
Fertilizer
Consumption
(LNFCONSP)
Mean
Median
Std. Dev.
Min
Max
N
0.17
0.16
0.07
0.04
0.35
238
10.86
10.84
1.68
8.12
14.20
239
1.05
0.73
0.70
0.29
3.20
210
2.46
0.68
4.31
0.00
29.51
89
10.30
10.29
1.47
8.21
12.78
178
3.76
3.41
2.48
0.28
11.08
82
0.35
0.00
2.07
-7.4
11.91
217
93.64
92.85
21.51
46.5
147.5
237
4.19
4.39
0.93
2.04
5.46
81
Source: Own composition from Food and Agriculture Organization Database
Carbon emissions are on average 1.05 KG per GDP share although less than
developed countries but these countries are affected by the emissions from other
developed countries. The mean agricultural foreign direct investment is 2.46 and
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Khalid, Mahmood and Rukh
its standard deviation is 4.31 that shows higher variation in the level of
Agricultural FDI share in total FDI. The Net Capital stock is showing the average
of 10.36 that means capital stock is higher than less developed economies but its
standard deviation is not higher and showing the value of 1.47. Finally, net
production index is showing the mean of 83.64 and its standard deviation is 21.51
that shows higher volatility in the production of agricultural products in these
countries.
Table 2: OLS Results of Climate Change and Gross Domestic Product and
Agricultural Value
CO2EM
AFDI
LNCST
AGEXP
AGARE
ANPI
LNFCONSP
Constant
Observations
F-test value
R-squared
LNGDP
1.55**
(0.67)
0.00
(0.02)
0.14
(0.27)
-0.11
(0.16)
0.16*
(0.09)
0.03*
(0.01)
0.30
(0.47)
4.87**
(2.32)
22
41.38
0.95
AVAGDP
0.00
(0.02)
-7.65
(0.00)
0.01**
(0.00)
-0.00
(0.00)
-0.00
(0.00)
-0.00
(0.00)
0.06***
(0.01)
-0.23***
(0.07)
22
106.80
0.982
Table 2 shows the OLS Pooled regression results (column 2 and 3) results for both LNGDP and
AVAGDP. The control variables includes, AFDI that depict FDI inflows to Agriculture, Forestry
and Fishing (Share of total FDI), LNCST is Natural log of Net Capital Stock (constant 2005
prices),AGEXP show central government expenditures on agriculture, forestry, fishing (Share of
total government expenditures), AGARE is percentage annual change in agricultural area, ANPI
show Agricultural Net Production Index Number (2004-2006 = 100), LNFCONSP is the Nitrogen
+ Phosphate Fertilizers use on permanent and arable crops, µi,t =represents error term, Standard
errors are in parentheses and *, **, *** indicate one tail statistical significance at the 1, 5, and 10%
levels, respectively.
Source: Own composition from Food and Agriculture Organization Database
Table 2 displays the results of OLS estimation using the dependent,
independent and control variables. Mainly we have checked the impact of climate
changes on the GDP and Agricultural value added to GDP. Table 2 shows the
results in two columns. First column shows the impact of climate changes on GDP
in these countries. The coefficient of our main independent variable CO2E is
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Khalid, Mahmood and Rukh
1.552 that is significant at 5% level. Its lower coefficient shows less economic
significance in the results and the direction of relationship is also against our
expectations in hypothesis 1. Table 3 displays the results of fixed estimation using
the dependent, independent and control variables. Mainly we have checked the
impact of climate changes on the GDP and Agricultural value added to GDP.
Table 3 shows the results in two columns. First column shows the impact of
climate changes on GDP in these countries. The coefficient of our main
independent variable CO2E is -0.747 that is significant at 1% level. Its high
coefficient indicates higher economic significance in the result supports our
hypothesis 1. In the second column in which we used Agriculture Value Added in
GDP proxy as dependent variable it displays the coefficient of 0.0553 that is
against our hypothesis but significant at 5% level. We have controlled the effect
of other variables in this study such as, LN fertilizer consumption have positive
influence on GDP and its coefficient is 0.135 but statistically insignificant. In the
second column with AVAGDP proxy LN Capital stock have surprisingly negative
influence on agricultural value added into share of GDP. In sum, we find support
to our hypothesis 1 that climate changes have adverse impact on the overall GDP
as because of these natural disasters these countries bear handsome amount as
losses but, this decrease in the GDP due to losses is not transferred to agricultural
sector as its value added share in the GDP is not reduced that may be due to nature
of these countries as they are prone to these changes in the external environment.
Table 3: Hausman Test Results of Climate Change and Gross Domestic
Product and Agricultural Value Added (Share in GDP)
Dependent
Variable
CO2EM
AFDI
LNCST
AGEXP
AGARE
ANPI
LNFCONSP
Constant
Observations
LNGDP
AVAGDP
Fixed Effects
-0.74***
0.05
(0.21)
(0.03)
0.00
-3.27
(0.00)
(0.00)
2.08**
-0.15
(0.90)
(0.15)
-0.00
-0.00
(0.02)
(0.00)
0.00
-0.00
(0.02)
(0.00)
0.00
0.00
(0.00)
(0.00)
0.13
-0.00
(0.11)
(0.01)
-11.13
1.76
(9.59)
(1.64)
22
22
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LNGDP
AVAGDP
Random Effects
1.55**
0.00
(0.67)
(0.02)
0.00
-7.65
(0.02)
(0.00)
0.14
0.01*
(0.27)
(0.00)
-0.11
-0.00
(0.16)
(0.00)
0.16*
-0.00
(0.09)
(0.00)
0.030
-0.00
(0.01)
(0.00)
0.30
0.06***
(0.47)
(0.01)
4.87**
-0.2***
(2.32)
(0.07)
22
22
44
Khalid, Mahmood and Rukh
Hausman P-Value
R-squared
0.0000
0.940
0.47
0.039
-
-
Table 5 shows the fixed effects results (column 2 and 3) and random effects (column 4 and 5)
results for both LNGDP and AVAGDP. These fixed and random effects tests are applied for
Hausman test calculation and selection of random or fixed effects method. In this table dependent
variables are AVAGDP is value Added, agriculture, forestry and fishing (Share of GDP, 2005
prices) and LNGDP is Natural log of Gross Domestic Product (US$, 2005),CO2EM is main
explanatory variable that shows Carbon dioxide emissions (kg per 2005 US$ of GDP), The control
variables includes, AFDI that depict FDI inflows to Agriculture, Forestry and Fishing (Share of
total FDI), LNCST is Natural log of Net Capital Stock (constant 2005 prices),AGEXP show central
government expenditures on agriculture, forestry, fishing (Share of total government
expenditures), AGARE is percentage annual change in agricultural area, ANPI show Agricultural
Net Production Index Number (2004-2006 = 100), LNFCONSP is the Nitrogen + Phosphate
Fertilizers use on permanent and arable crops, µi,t =represents error term, Standard errors are in
parentheses and *, **, *** indicate statistical significance at the 1, 5, and 10% levels, respectively.
Source: Own composition from Food and Agriculture Organization Database
Table 4: Fixed Effects Results of Climate Change and Gross Domestic
Product and Agricultural Value Added (Share in GDP)
CO2EM
AFDI
LNCST
AGEXP
AGARE
ANPI
LNFCONSP
Constant
Observations
R-squared
LNGDP
-0.747***
(0.215)
0.004
(0.003)
2.088**
(0.909)
-0.007
(0.021)
0.002
(0.0217)
0.003
(0.0041)
0.135
(0.113)
-11.13
(9.597)
22
0.954
AVAGDP
0.0553**
(0.036)
-3.270
(0.0006)
-0.157
(0.156)
-0.004
(0.003)
-0.0007
(0.003)
0.0007
(0.0007)
-0.006
(0.0194)
1.766
(1.645)
22
0.982
Table 4 shows the fixed effects results (column 2 and 3) results for both LNGDP and AVAGDP. In
this table dependent variables are AVAGDP is value Added, agriculture, forestry and fishing
(Share of GDP, 2005 prices) and LNGDP is Natural log of Gross Domestic Product (US$,
2005),CO2EM is main explanatory variable that shows Carbon dioxide emissions (kg per 2005
US$ of GDP), The control variables includes, AFDI that depict FDI inflows to Agriculture,
Forestry and Fishing (Share of total FDI), LNCST is Natural log of Net Capital Stock (constant
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Khalid, Mahmood and Rukh
2005 prices),AGEXP show central government expenditures on agriculture, forestry, fishing
(Share of total government expenditures), AGARE is percentage annual change in agricultural area,
ANPI show Agricultural Net Production Index Number (2004-2006 = 100), LNFCONSP is the
Nitrogen + Phosphate Fertilizers use on permanent and arable crops, µi,t =represents error term,
Standard errors are in parentheses and *, **, *** indicate one tail statistical significance at the 10,
5, and 1% levels, respectively.
Source: Own composition from Food and Agriculture Organization Database
CONCLUSION
The results suggests that climate changes have adverse impacts on the GDP of
these countries. But, these effects are positive with Agriculture value added GDP
as dependent variable. These changes in the climate increase the frequency of
floods, heat waves and storms in these countries those are most vulnerable to
these events due to geographical structure. We find support to our hypothesis that
climate changes reduce the GDP in these countries as they suffer the huge losses
due to these natural disasters. These changes in the climate also reduce the
agricultural crop production as weather patterns are changing in these days due to
higher carbon emissions. However, we find no support for the effect of climate
changes on Agriculture value added. Perhaps, the share of GDP may be due to
lower contribution of agriculture sector to overall GDP of these countries. Mainly,
we contribute towards existing literature by examining the effect of climate
changes in the most affected countries by gathering data from 1990-2013. Our
findings suggest that policies should be designed to increase the savings. The
other policies can be adapted at regional and global level for reduction of
greenhouse gas emissions as the rise in temperature is a threat for the agricultural
and health sector of these countries.
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APPENDIX
Table 6: Variables Definitions
Variables
Definitions
Agri Value Added (Share in GDP) Value Added, Agriculture, Forestry and
Fishing (Share of GDP, 2005 prices)
Natural Log GDP (Current US$
Natural log of Gross Domestic Product
2005)
(US$, 2005)
CO2 Emissions (KG per GDP)
(CO2) Carbon dioxide emissions
Agriculture FDI
FDI inflows to Agriculture, Forestry and
Fishing
Natural Log Capital Stock
Natural log of Net Capital Stock
(constant 2005 prices)
Agri Expenditures
Central government expenditures on
Agriculture, forestry, fishing (Share of
total government expenditures)
Agricultural Area
Percentage annual change in agricultural
area
Agri Net Production Index
Agricultural Net Production Index
Number (2004-2006 = 100)
Natural Log Fertilizer
Nitrogen + Phosphate Fertilizers use on
Consumption
permanent and arable crops.
Pairwise correlation matrix in which * indicates significance at 5% level.
Table 7: List of Countries
Serial#
Country Names
Time Span
1
Bangladesh
1990-2013
2
Dominican Republic
1990-2013
3
Guatemala
1990-2013
4
Haiti
1990-2013
5
India
1990-2013
6
Nicaragua
1990-2013
7
Pakistan
1990-2013
8
Philippines
1990-2013
9
Russian Federation
1990-2013
10
Vietnam
1990-2013
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