Effects of CPI on GDP: Analysis and Regression Model
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This article analyzes the effects of CPI on GDP using regression analysis. The study uses secondary data from the Australian Bureau of Statistics and shows a negative relationship between CPI and GDP. The article suggests that reducing CPI is crucial for increasing GDP.
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Running Header: What are the effects of CPI on GDP? 1
What are the effects of CPI on GDP?
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What are the effects of CPI on GDP? 2
INTRODUCTION
In most cases, the economic growth is measured using the Gross Domestic Product (GDP). The
advancement in all fields of a nation can be provided normally using the economic growth of a
country (Olson, 2008). Generally, the Gross Domestic Product grows faster when business takes
on more labor thereby giving the residents more money to spend (Vassalou, 2003). As a result,
there is an increase in demand for the availability of money to spend on needs and wants. On the
contrary, when there is no economic growth, business will become stagnant or even downsized.
Employment will become inactive or even shrink as the demand and the living standards of the
people are affected adversely.
Gross Domestic Product is the worth of money of all the final goods and services which are
produced from sale in one year within a nation (Auty, 2003). Gross Domestic Product is
measured using three ways. They include the income, the production, and the expenditure
approach. Use of the measures is bound to lead to the same result (Stewart & Rankin, 2008).
Gross Domestic Product includes exports but does not include expenditure on imports.
The Gross Domestic Product value that is unadjusted for inflation, which measures in current
instead of base-period dollars, is referred to as Nominal Gross Domestic Product (Mariano &
Ozmucur, 2018). The value of Gross Domestic Product that is expressed in the dollars base
period while eliminating the impact of changes in price is referred to as the Real Gross Domestic
Product. When the actual quantities of output remain the same, the Real Gross Domestic Product
will remain unchanged. However, the nominal Gross Domestic Product may increase or decrease
in correlation with the rising or falling prices of goods and services (Mielnik & Goldermberg,
2002). The progression in real Gross Domestic Product over a period is a sign of the
INTRODUCTION
In most cases, the economic growth is measured using the Gross Domestic Product (GDP). The
advancement in all fields of a nation can be provided normally using the economic growth of a
country (Olson, 2008). Generally, the Gross Domestic Product grows faster when business takes
on more labor thereby giving the residents more money to spend (Vassalou, 2003). As a result,
there is an increase in demand for the availability of money to spend on needs and wants. On the
contrary, when there is no economic growth, business will become stagnant or even downsized.
Employment will become inactive or even shrink as the demand and the living standards of the
people are affected adversely.
Gross Domestic Product is the worth of money of all the final goods and services which are
produced from sale in one year within a nation (Auty, 2003). Gross Domestic Product is
measured using three ways. They include the income, the production, and the expenditure
approach. Use of the measures is bound to lead to the same result (Stewart & Rankin, 2008).
Gross Domestic Product includes exports but does not include expenditure on imports.
The Gross Domestic Product value that is unadjusted for inflation, which measures in current
instead of base-period dollars, is referred to as Nominal Gross Domestic Product (Mariano &
Ozmucur, 2018). The value of Gross Domestic Product that is expressed in the dollars base
period while eliminating the impact of changes in price is referred to as the Real Gross Domestic
Product. When the actual quantities of output remain the same, the Real Gross Domestic Product
will remain unchanged. However, the nominal Gross Domestic Product may increase or decrease
in correlation with the rising or falling prices of goods and services (Mielnik & Goldermberg,
2002). The progression in real Gross Domestic Product over a period is a sign of the
What are the effects of CPI on GDP? 3
performance of an economy (Sutton et al., 2007). An appropriate gauge of living standards is the
real GDP per capita that is the real GDP divided by the population.
In Australia, price stability is measured using the index of price. The price index is a series of
price measurements which show how the mean price of a set of goods changes over time (Nath
& Sarkar, 2018). The most vital price indices are the Producers Price Index (PPI) and Consumer
Price Index (CPI). CPI is a degree of the general price levels of goods and services which are
purchased by households. Consequently, Producers Price Index (PPI) is a measure which is not
confined to those items that are bought by households and includes all goods and services that
are produced in Australia (Khan et al., 2018). It should be noted that the percentage change in an
index and the direction of the change matters instead of the index number itself.
HYPOTHESES
To test the relationship between the GDP percentage change and the CPI, a hypothesis was
developed. A hypothesis is a statement which tests a relationship between two or more variables
(Chen et al., 2008). In a study or experiment, a hypothesis briefly sums a researcher’s prediction
of the findings of the study which may be or not supported by the outcome. A hypothesis entails
a null hypothesis and an alternate hypothesis (Craig & Abramson, 2018). A null hypothesis is a
hypothesis of no difference. Thus, a null hypothesis suggests that there is a relationship between
two or more variables. On the other hand, an alternate hypothesis is a hypothesis that shows that
there is a difference between two or more variables. Thus, acceptance of an alternate hypothesis
shows that there is no relationship between two or more variables.
Thus;
performance of an economy (Sutton et al., 2007). An appropriate gauge of living standards is the
real GDP per capita that is the real GDP divided by the population.
In Australia, price stability is measured using the index of price. The price index is a series of
price measurements which show how the mean price of a set of goods changes over time (Nath
& Sarkar, 2018). The most vital price indices are the Producers Price Index (PPI) and Consumer
Price Index (CPI). CPI is a degree of the general price levels of goods and services which are
purchased by households. Consequently, Producers Price Index (PPI) is a measure which is not
confined to those items that are bought by households and includes all goods and services that
are produced in Australia (Khan et al., 2018). It should be noted that the percentage change in an
index and the direction of the change matters instead of the index number itself.
HYPOTHESES
To test the relationship between the GDP percentage change and the CPI, a hypothesis was
developed. A hypothesis is a statement which tests a relationship between two or more variables
(Chen et al., 2008). In a study or experiment, a hypothesis briefly sums a researcher’s prediction
of the findings of the study which may be or not supported by the outcome. A hypothesis entails
a null hypothesis and an alternate hypothesis (Craig & Abramson, 2018). A null hypothesis is a
hypothesis of no difference. Thus, a null hypothesis suggests that there is a relationship between
two or more variables. On the other hand, an alternate hypothesis is a hypothesis that shows that
there is a difference between two or more variables. Thus, acceptance of an alternate hypothesis
shows that there is no relationship between two or more variables.
Thus;
What are the effects of CPI on GDP? 4
H0: There is an association between percentage change in GDP and CPI
H1: There is no association between percentage change in GDP and CPI
TREND AND DESCRIPTIVE ANALYSIS
Gross Domestic Product
Figure 1: Gross Domestic Product Trend
Table 1: GDP descriptive statistics
Mean 0.86
Standard Error 0.04
Median 0.8
Mode 0.9
Standard
Deviation 0.60
De c - 1 9 5 9
S e p- 1 9 6 1
J un- 1 9 63
Ma r- 1 9 6 5
De c - 1 9 6 6
S e p- 1 9 6 8
J un- 1 9 70
Ma r- 1 9 7 2
De c - 1 9 7 3
S e p- 1 9 7 5
J un- 1 9 77
Ma r- 1 9 7 9
De c - 1 9 8 0
S e p- 1 9 8 2
J un- 1 9 84
Ma r- 1 9 8 6
De c - 1 9 8 7
S e p- 1 9 8 9
J un- 1 9 91
Ma r- 1 9 9 3
De c - 1 9 9 4
S e p- 1 9 9 6
J un- 1 9 98
Ma r- 2 0 0 0
De c - 2 0 0 1
S e p- 2 0 0 3
J un- 2 0 05
Ma r- 2 0 0 7
De c - 2 0 0 8
S e p- 2 0 1 0
J un- 2 0 12
Ma r- 2 0 1 4
De c - 2 0 1 5
S e p- 2 0 1 7
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
GDP
H0: There is an association between percentage change in GDP and CPI
H1: There is no association between percentage change in GDP and CPI
TREND AND DESCRIPTIVE ANALYSIS
Gross Domestic Product
Figure 1: Gross Domestic Product Trend
Table 1: GDP descriptive statistics
Mean 0.86
Standard Error 0.04
Median 0.8
Mode 0.9
Standard
Deviation 0.60
De c - 1 9 5 9
S e p- 1 9 6 1
J un- 1 9 63
Ma r- 1 9 6 5
De c - 1 9 6 6
S e p- 1 9 6 8
J un- 1 9 70
Ma r- 1 9 7 2
De c - 1 9 7 3
S e p- 1 9 7 5
J un- 1 9 77
Ma r- 1 9 7 9
De c - 1 9 8 0
S e p- 1 9 8 2
J un- 1 9 84
Ma r- 1 9 8 6
De c - 1 9 8 7
S e p- 1 9 8 9
J un- 1 9 91
Ma r- 1 9 9 3
De c - 1 9 9 4
S e p- 1 9 9 6
J un- 1 9 98
Ma r- 2 0 0 0
De c - 2 0 0 1
S e p- 2 0 0 3
J un- 2 0 05
Ma r- 2 0 0 7
De c - 2 0 0 8
S e p- 2 0 1 0
J un- 2 0 12
Ma r- 2 0 1 4
De c - 2 0 1 5
S e p- 2 0 1 7
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
GDP
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What are the effects of CPI on GDP? 5
Figure 1 shows that the percentage change of GDP has been fluctuating frequently over the
quarters. The highest GDP percentage change that has been achieved over the quarters was in
July 1969 with a percentage change of 2.5%. On the other hand, the lowest Gross Domestic
Product percentage change over the quarters was in December 1982 with a low of -1.2%. The
mean percentage change of Gross Domestics Product was 0.86% with a standard deviation of
0.6%.
Consumer Price Index
De c - 1 9 59
S e p- 1 9 61
J un- 1 9 63
Ma r- 1 9 65
De c - 1 9 66
S e p- 1 9 68
J un- 1 9 70
Ma r- 1 9 72
De c - 1 9 73
S e p- 1 9 75
J un- 1 9 77
Ma r- 1 9 79
De c - 1 9 80
S e p- 1 9 82
J un- 1 9 84
Ma r- 1 9 86
De c - 1 9 87
S e p- 1 9 89
J un- 1 9 91
Ma r- 1 9 93
De c - 1 9 94
S e p- 1 9 96
J un- 1 9 98
Ma r- 2 0 00
De c - 2 0 01
S e p- 2 0 03
J un- 2 0 05
Ma r- 2 0 07
De c - 2 0 08
S e p- 2 0 10
J un- 2 0 12
Ma r- 2 0 14
De c - 2 0 15
S e p- 2 0 17
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
CPI
Figure 2: Consumer Price Index trend
Table 2: Consumer Price Index Descriptive Statistics
A similar observation could also be observed for the CPI. The
CPI reached its highest point in December 1977 with a high of 6.1%. On the other hand, the CPI
Mean 1.18
Standard Error 0.07
Median 0.9
Mode 0
Standard Deviation 1.11
Figure 1 shows that the percentage change of GDP has been fluctuating frequently over the
quarters. The highest GDP percentage change that has been achieved over the quarters was in
July 1969 with a percentage change of 2.5%. On the other hand, the lowest Gross Domestic
Product percentage change over the quarters was in December 1982 with a low of -1.2%. The
mean percentage change of Gross Domestics Product was 0.86% with a standard deviation of
0.6%.
Consumer Price Index
De c - 1 9 59
S e p- 1 9 61
J un- 1 9 63
Ma r- 1 9 65
De c - 1 9 66
S e p- 1 9 68
J un- 1 9 70
Ma r- 1 9 72
De c - 1 9 73
S e p- 1 9 75
J un- 1 9 77
Ma r- 1 9 79
De c - 1 9 80
S e p- 1 9 82
J un- 1 9 84
Ma r- 1 9 86
De c - 1 9 87
S e p- 1 9 89
J un- 1 9 91
Ma r- 1 9 93
De c - 1 9 94
S e p- 1 9 96
J un- 1 9 98
Ma r- 2 0 00
De c - 2 0 01
S e p- 2 0 03
J un- 2 0 05
Ma r- 2 0 07
De c - 2 0 08
S e p- 2 0 10
J un- 2 0 12
Ma r- 2 0 14
De c - 2 0 15
S e p- 2 0 17
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
CPI
Figure 2: Consumer Price Index trend
Table 2: Consumer Price Index Descriptive Statistics
A similar observation could also be observed for the CPI. The
CPI reached its highest point in December 1977 with a high of 6.1%. On the other hand, the CPI
Mean 1.18
Standard Error 0.07
Median 0.9
Mode 0
Standard Deviation 1.11
What are the effects of CPI on GDP? 6
was at its lowest point in December 1961 with a low of -1.3%. The Consumer Price Index has a
mean of 1.18% with a standard deviation of 1.11%.
TESTING OF HYPOTHESES
Sources of data
Data used in this study was secondary in nature and was thereby obtained from existing sources.
Thus, it was acquired from the Australian Bureau of Statistics.
Data collection
The model of estimation was done using quarterly historical data. The data ranged from
December 1959 to December 2017. The period was selected to capture the trends of the
measures over the 58 year period. Therefore, the study adopted a time series data.
REGRESSION ANALYSIS
To test the developed hypothesis, the statistical method that was appropriate was a linear
regression model. The main idea behind regression analysis is examining whether a set of
predictor variables do a good job in predicting a dependent (outcome) variable (Kutner et al.,
2004). Conversely, it tests whether a variable, in particular, is a significant predictor of the
outcome variable. It tests the magnitude of the predictor variable and the sign of beta estimates
which affect impact the variable outcome. In a nutshell, a regression analysis determines the
strength of the predictor, forecasts an effect and forecasts the trend.
was at its lowest point in December 1961 with a low of -1.3%. The Consumer Price Index has a
mean of 1.18% with a standard deviation of 1.11%.
TESTING OF HYPOTHESES
Sources of data
Data used in this study was secondary in nature and was thereby obtained from existing sources.
Thus, it was acquired from the Australian Bureau of Statistics.
Data collection
The model of estimation was done using quarterly historical data. The data ranged from
December 1959 to December 2017. The period was selected to capture the trends of the
measures over the 58 year period. Therefore, the study adopted a time series data.
REGRESSION ANALYSIS
To test the developed hypothesis, the statistical method that was appropriate was a linear
regression model. The main idea behind regression analysis is examining whether a set of
predictor variables do a good job in predicting a dependent (outcome) variable (Kutner et al.,
2004). Conversely, it tests whether a variable, in particular, is a significant predictor of the
outcome variable. It tests the magnitude of the predictor variable and the sign of beta estimates
which affect impact the variable outcome. In a nutshell, a regression analysis determines the
strength of the predictor, forecasts an effect and forecasts the trend.
What are the effects of CPI on GDP? 7
As a result, the regression estimates are utilized in explaining the relationship between one
dependent variable and one or more variables which are independent.
The simplest regression equation form is defined by the formula:
Y = c +bx
Y estimates the score of the dependent variable: c is the constant: b is the coefficient of
regression while x is the score of the independent variable.
The linear regression that was used in determining the relationship between the Gross Domestic
Product percentage change and Consumer Price Index was developed through Microsoft Excel.
The outputs are as shown in the subsequent tables below.
Table 3: Regression Statistics
Multiple R R Square Adjusted R Square Standard Error Observations
0.22 0.05 0.04 0.59 233
From the table 3 above, it can be seen that the regression model explains 4% of the variability.
Consequently, 96% of the variability is explained by variables which are not in the model. From
this, it can also be deduced that the regression model fits a straight line.
Table 4: ANOVA
Degree of freedom Sum of Squares Mean of Squares F Significance F
Regression 1 4.00 4.00 11.67 0.00
Residual 231 79.25 0.34
Total 232 83.25
The ANOVA table shows that the regression model is statistically significant. The model has a
significant level of 0.00 which is less than the critical acceptance value of 0.05.
As a result, the regression estimates are utilized in explaining the relationship between one
dependent variable and one or more variables which are independent.
The simplest regression equation form is defined by the formula:
Y = c +bx
Y estimates the score of the dependent variable: c is the constant: b is the coefficient of
regression while x is the score of the independent variable.
The linear regression that was used in determining the relationship between the Gross Domestic
Product percentage change and Consumer Price Index was developed through Microsoft Excel.
The outputs are as shown in the subsequent tables below.
Table 3: Regression Statistics
Multiple R R Square Adjusted R Square Standard Error Observations
0.22 0.05 0.04 0.59 233
From the table 3 above, it can be seen that the regression model explains 4% of the variability.
Consequently, 96% of the variability is explained by variables which are not in the model. From
this, it can also be deduced that the regression model fits a straight line.
Table 4: ANOVA
Degree of freedom Sum of Squares Mean of Squares F Significance F
Regression 1 4.00 4.00 11.67 0.00
Residual 231 79.25 0.34
Total 232 83.25
The ANOVA table shows that the regression model is statistically significant. The model has a
significant level of 0.00 which is less than the critical acceptance value of 0.05.
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What are the effects of CPI on GDP? 8
Table 5: Regression Model
From the regression model, it is evident that all factors kept constant, the Gross Domestic
Product percentage change is 1 unit. The constant is statistically significant at p < 0.05.
Conversely, a unit increase in the Consumer Price Index leads to a 0.12 decrease in the Gross
Domestic Product percentage change. Consequently, the change is statistically significant at p <
0.05.
Interpretation
From the regression model, the mathematical model that is derived is:
GDP = 1 – 0.12CPI
Therefore, we can deduce that the relationship between the Gross Domestic Product percentage
change and Consumer Price Index is negative. Thus, when the CPI increases, the percentage
change in GDP tends to decrease. The opposite is also true.
The regression model, therefore, supports existing literature which claim that the Consumer Price
Index contributes negatively to the Gross Domestic Product of a nation. Therefore, for a nation
to ensure that its Gross Domestic Product continues to grow significantly, and then it has to
reduce the Consumer Price Index. The reduction can be achieved through the reduction of costs
of basic goods and commodities thereby making the living standards of the people attainable to
all.
Coefficients Standard Error t Stat P-value
Intercept 1.00 0.06 17.78 0.00
CPI -0.12 0.03 -3.42 0.00
Table 5: Regression Model
From the regression model, it is evident that all factors kept constant, the Gross Domestic
Product percentage change is 1 unit. The constant is statistically significant at p < 0.05.
Conversely, a unit increase in the Consumer Price Index leads to a 0.12 decrease in the Gross
Domestic Product percentage change. Consequently, the change is statistically significant at p <
0.05.
Interpretation
From the regression model, the mathematical model that is derived is:
GDP = 1 – 0.12CPI
Therefore, we can deduce that the relationship between the Gross Domestic Product percentage
change and Consumer Price Index is negative. Thus, when the CPI increases, the percentage
change in GDP tends to decrease. The opposite is also true.
The regression model, therefore, supports existing literature which claim that the Consumer Price
Index contributes negatively to the Gross Domestic Product of a nation. Therefore, for a nation
to ensure that its Gross Domestic Product continues to grow significantly, and then it has to
reduce the Consumer Price Index. The reduction can be achieved through the reduction of costs
of basic goods and commodities thereby making the living standards of the people attainable to
all.
Coefficients Standard Error t Stat P-value
Intercept 1.00 0.06 17.78 0.00
CPI -0.12 0.03 -3.42 0.00
What are the effects of CPI on GDP? 9
CONCLUSION
The CPI is widely used as a measure of inflation and a proxy of the efficiency of the
government’s economic policy. It gives citizens, businesses and the government an idea of the
changes in price in the economy and as a guide in making informed decisions regarding the
economy. Thus, ensuring a low Consumer Price Index is a great starting point in ensuring that
Australia is able to increase its Gross Domestic Product in the subsequent quarters or years to
come.
CONCLUSION
The CPI is widely used as a measure of inflation and a proxy of the efficiency of the
government’s economic policy. It gives citizens, businesses and the government an idea of the
changes in price in the economy and as a guide in making informed decisions regarding the
economy. Thus, ensuring a low Consumer Price Index is a great starting point in ensuring that
Australia is able to increase its Gross Domestic Product in the subsequent quarters or years to
come.
What are the effects of CPI on GDP? 10
REFERENCES
Auty, R.M. ed., 2001. Resource abundance and economic development. Oxford University Press.
Chen, F., Curran, P.J., Bollen, K.A., Kirby, J. and Paxton, P., 2008. An empirical evaluation of
the use of fixed cutoff points in RMSEA test statistic in structural equation
models. Sociological methods & research, 36(4), pp.462-494.
Craig, D.P.A. and Abramson, C.I., 2018. Ordinal pattern analysis in comparative psychology-A
flexible alternative to null hypothesis significance testing using an observation oriented
modeling paradigm. International Journal of Comparative Psychology, 31.
Khan, K., Su, C.W., Tao, R. and Lobonț, O.R., 2018. PRODUCER PRICE INDEX AND
CONSUMER PRICE INDEX: CAUSALITY IN CENTRAL AND EASTERN
EUROPEAN COUNTRIES. Ekonomický časopis (Journal of Economics), 66(4).
Kutner, M.H., Nachtsheim, C. and Neter, J., 2004. Applied linear regression models. McGraw-
Hill/Irwin.
Mariano, R.S. and Ozmucur, S., 2018. High-mixed-frequency forecasting models for GDP and
inflation. Global Economic Modeling: A Volume In Honor Of Lawrence R Klein, p.2.
REFERENCES
Auty, R.M. ed., 2001. Resource abundance and economic development. Oxford University Press.
Chen, F., Curran, P.J., Bollen, K.A., Kirby, J. and Paxton, P., 2008. An empirical evaluation of
the use of fixed cutoff points in RMSEA test statistic in structural equation
models. Sociological methods & research, 36(4), pp.462-494.
Craig, D.P.A. and Abramson, C.I., 2018. Ordinal pattern analysis in comparative psychology-A
flexible alternative to null hypothesis significance testing using an observation oriented
modeling paradigm. International Journal of Comparative Psychology, 31.
Khan, K., Su, C.W., Tao, R. and Lobonț, O.R., 2018. PRODUCER PRICE INDEX AND
CONSUMER PRICE INDEX: CAUSALITY IN CENTRAL AND EASTERN
EUROPEAN COUNTRIES. Ekonomický časopis (Journal of Economics), 66(4).
Kutner, M.H., Nachtsheim, C. and Neter, J., 2004. Applied linear regression models. McGraw-
Hill/Irwin.
Mariano, R.S. and Ozmucur, S., 2018. High-mixed-frequency forecasting models for GDP and
inflation. Global Economic Modeling: A Volume In Honor Of Lawrence R Klein, p.2.
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What are the effects of CPI on GDP? 11
Mielnik, O. and Goldemberg, J., 2002. Foreign direct investment and decoupling between energy
and gross domestic product in developing countries. Energy policy, 30(2), pp.87-89.
Nath, H.K. and Sarkar, J., 2018. Inflation and relative price variability: new evidence from
survey-based measures of inflation expectations in Australia. Empirical Economics, pp.1-
24.
Olson, M., 2008. The rise and decline of nations: Economic growth, stagflation, and social
rigidities. Yale University Press.
Stewart, J. and Rankin, K., 2008. Economic concepts and applications: the contemporary New
Zealand environment. Pearson.
Sutton, P.C., Elvidge, C.D. and Ghosh, T., 2007. Estimation of gross domestic product at sub-
national scales using nighttime satellite imagery. International Journal of Ecological
Economics & Statistics, 8(S07), pp.5-21.
Vassalou, M., 2003. News related to future GDP growth as a risk factor in equity
returns. Journal of financial economics, 68(1), pp.47-73.
Mielnik, O. and Goldemberg, J., 2002. Foreign direct investment and decoupling between energy
and gross domestic product in developing countries. Energy policy, 30(2), pp.87-89.
Nath, H.K. and Sarkar, J., 2018. Inflation and relative price variability: new evidence from
survey-based measures of inflation expectations in Australia. Empirical Economics, pp.1-
24.
Olson, M., 2008. The rise and decline of nations: Economic growth, stagflation, and social
rigidities. Yale University Press.
Stewart, J. and Rankin, K., 2008. Economic concepts and applications: the contemporary New
Zealand environment. Pearson.
Sutton, P.C., Elvidge, C.D. and Ghosh, T., 2007. Estimation of gross domestic product at sub-
national scales using nighttime satellite imagery. International Journal of Ecological
Economics & Statistics, 8(S07), pp.5-21.
Vassalou, M., 2003. News related to future GDP growth as a risk factor in equity
returns. Journal of financial economics, 68(1), pp.47-73.
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