The Relationship Between Inflation And Cereal Export In Australia

Past Studies on Economic Growth and Export Relationship

International trade is on important contributor of Australian economy. Australia though rich in mineral resource but still agricultural products are in the list of main exported commodity of Australia. Australia is one of the most important producers and exporters of the world (Mansfield & Reinhardt, 2015). Export of cereal and cereal preparation constitute an important part of primary export. Inflation signifies a fast revolutionize in the cost of product. During inflation, value of money reduces leading to a reduction in purchasing power of people. High inflation or rising commodity price may not be favorable for Australia. It though can provide short term benefits to the exporters but in the long run it hurts export by increasing uncertainty about movement of price level (Gilpin, 2016).

            Export earnings provides an additional source of income to the exporting industry and nation as a whole. Goods are exchanged at their relative prices determined by the exchange rate in the foreign exchange market (Vahlne & Johanson, 2017). The paper evaluates relation between inflation and export of cereals along with examining relation of concerned attributes with exchange rate and overall state of the economy.

1.2 Research aim and research questions

            The research paper aims to find out the relation between rate of inflation in Australia and cereal export. In relation to this, the paper analyzes the effect of cereal exports on Australian economy. Inflation influences export through exchange rate channel. In this context, the paper also evaluates the relation of inflation rate with exchange rate. Export demand of a nation depends on the relative value of currency.

 In particular, the research aims to address the following questions

1. i) How cereal export affects Australian economy?
2. ii) How inflation influences exchange rate?

iii) What is the relation between inflation and cereal export?

2. Literature review

            This sections evaluates some of the past studies related to current research area. This will provide a deep understanding about the chosen field of research. The paper draws insight from different research projects and analyzes whether obtained results support the past hypothesis or not.

2.1 Export as a driver of economic growth

            There are several studies that analyzes role of export on economic growth (Abdurehman & Hacilar, 2016). A study conducted by Kalaitzi examines economic growth and export relationship for United Arab Emirates for the period 1980-2010. The concerned paper tested long term relationship between growth and export using Engel Granger co-integration test. Result of this study found an existence of a long-term relationship between economic growth and that of primary and manufacturing export. The study confirmed that further diversification of export would accelerate growth of UAE (Kalaitzi, 2013).

Pass Through Effect of Exchange Rate and Inflation

            A paper presented by Ahdi et al. (2013) examine dynamic relation between export and economic prosperity using tools of linear and non-linear causality test prepared by Engel Granger. The study was based on South African data on real gross domestic product and real export for the sample period 1911-2011. The linear causality test did not find any significant relation between GDP and export. The non-linear causality test however revealed a unidirectional relation from GDP to export (Ahdi et al., 2013).

2.2 Relation between exchange rate and inflation

            There might exists a two dimensional relationship between inflation and exchange rate. That is inflation is a factor that affects exchange rate (Shihab, Soufan & Abdul-Khaliq, 2014). At the same time, it might also be a factor that is affected by exchange rate. Studies have found that exchange rate generally pass through prices. The pass through effect is larger for countries experiencing a higher inflation (Belloumi, 2014). Arslaner et al. (2014) examined pass through effects of inflation for Turkey taking data from 1986 to 2013. Result showed that like others developing nations, a pass through effect of exchange rate exists for Turkey as well. This effect was found to be more intense for Turkey in comparison to other developed nations (Arslaner et al., 2014). Another interest finding was that the pass through effect is smaller for consumer price index (CPI) than that for producer price index (PPI). The pass through effect is particularly relevant to currency crisis occurred in the past and economic openness (MacDonald et al., 2015).

            The co-efficient of pass through effect found to be statistically significant during crisis. Co-efficient found to be lower impact during crisis while it has a higher impact in times of crisis (He, Brouthers & Filatotchev, 2018). Exclusion of crisis data provided a smaller co-efficient. A volatile relationship had been found between exchange rate and volatility in the price level (Bussière, Delle Chiaie & Peltonen, 2014).

2.3 Inflation and agricultural export

            In a globalized world inflation has become an important aspect for nations to build their trading block by improving terms of trade condition (Ozkan, 2013). Nations participate in trade to meet the excess of domestic demand at a relatively cheap price and sell their product to the external market at a higher price. Therefore, price level should be stable to allow the nations to get cheaper inputs or raw materials from neighboring countries (Ghosh, Ostry & Chamon, 2016).

Role of Inflation in Building Trading Blocks

            Malik & Chowdhury (2011) used a multivariate GARCH model to establish a relation between growth and associated uncertainty with inflation and inflation uncertainty with growth. For this quarterly data on output growth was used. Result found a strong relation between inflation and growth uncertainty. The ongoing inflation leads to inflation uncertainty bring further instability in growth (Malik & Chowdhury, 2011).

            Empirical research found a positive significant relation between inflation and export of primary product. The research provided useful insight about CPI inflation and export growth. Higher inflation thus supports export growth (Auer, 2015).

2.4 Hypothesis

            In order address the research question following three hypotheses are framed

Hypothesis 1

Null Hypothesis (H0): No significant relation exists between cereal export and GDP of Australia.

Alternative Hypothesis (H1): A statistically significant relation exists between cereal export and GDP of Australia.

Hypothesis 2

Null Hypothesis (H0): No significant relation exists between rate of inflation and exchange rate of Australia.

Alternative Hypothesis (H1): A statistically significant relation exists between rate of inflation and exchange rate of Australia.

Hypothesis 3

Null Hypothesis (H0): No significant relation exists between cereal export and rate of inflation in Australia.

Alternative Hypothesis (H1): A statistically significant relation exists between cereal export and rate of inflation in Australia.

3. Methodology

3.1 Data collection

            The paper designed to study the relationship between inflation and cereals export of Australia. It also evaluates effect on cereal export on Australian economy and corresponding relationship between inflation and exchange rate.  The research is based on secondary data. Data are collected from official websites on Australian bureau of Statistics, world bank and other authentic sources. The chosen sample period for the study extended from 2000 to 2016. Data on cereal and cereal preparation exports are collected from Australian Bureau of Statistics. Relevant data for Gross Domestic Product and inflation is obtained from World Bank. Finally, the data on exchange rate between Australia and USA is are collected from ABS website.

3.2 Data Analysis

            The collected data are then analyzed using statistical software tool of SPSS. Descriptive statistics, bivariate correlation and regression is used to analyze the data and drive certain conclusion.

3.2.1 Export and economic growth

            Bivariate correlation is used to find degree of association between the two variables. In order to establish a causal relationship between export and economic growth a bivariate linear regression is run between the two variable taking GDP as dependent variable and cereal export as independent variable.

3.2.2 Inflation and exchange rate

Bivariate correlation   is used to find degree of association between the two variables. In order to establish the influence of inflation on exchange rate a bivariate linear regression is run between the two variable taking exchange rate as dependent variable and inflation as independent variable.

3.2.3 Inflation and cereal export

            Association between inflation and cereal export is found from the bivariate correlation between inflation and cereal export. In order to estimate a relation between inflation and cereal export a linear regression model is built. In the regression analysis cereal export is taken as dependent variable and inflation is taken as independent variable.

4. Findings and Analysis

4.1 Descriptive Statistics

Table 1: Descriptive statistics of GDP, inflation and Cereal export

Statistics
	GDP	Inflation	Exchange_rate	Cereal_export
N	Valid	17	17	17	17
Missing	0	0	0	0
Mean	1087483.8822	2.7835	1.3271	58.2612
Std. Error of Mean	38389.64618	.23672	.06930	6.77128
Median	1100462.9220	2.6700	1.3100	63.6700
Mode	847014.44a	1.28a	.97a	24.67a
Std. Deviation	158284.56614	.97603	.28572	27.91869
Variance	25054003878.129	.953	.082	779.453
Skewness	.018	.434	.855	.395
Std. Error of Skewness	.550	.550	.550	.550
Kurtosis	-1.190	-.546	.068	-1.071
Std. Error of Kurtosis	1.063	1.063	1.063	1.063
Range	496166.79	3.20	.96	81.25
Minimum	847014.44	1.28	.97	24.67
Maximum	1343181.24	4.48	1.93	105.92
Sum	18487226.00	47.32	22.56	990.44
a. Multiple modes exist. The smallest value is shown

 Descriptive statistics provide an overall summary measure of the chosen variable (Hox, Moerbeek & van de Schoot, 2017). The mean value of GDP is obtained as 1087483.88 billion. This indicates GDP of Australia in the last 17 years averaged at 1087483.88 billion. The average inflation rate for the chosen sample period is 2.78 percent. Mean exchange rate in the given period is 1.32. Australia, in the last 17 years exported cereals with an average worth of 58.2612 million. Standard deviation for all the four chosen variables is less than their average value. Standard deviation lower than mean value indicates a relatively stable distribution.

4.2 Correlation Analysis

Table 2: Correlation between inflation, exchange rate and GDP

Correlations
	GDP	Inflation	Exchange_rate	Cereal_export
GDP	Pearson Correlation	1	-.664**	-.735**	.979**
Sig. (2-tailed)		.004	.001	.000
N	17	17	17	17
Inflation	Pearson Correlation	-.664**	1	.426	-.623**
Sig. (2-tailed)	.004		.088	.008
N	17	17	17	17
Exchange_rate	Pearson Correlation	-.735**	.426	1	-.620**
Sig. (2-tailed)	.001	.088		.008
N	17	17	17	17
Cereal_export	Pearson Correlation	.979**	-.623**	-.620**	1
Sig. (2-tailed)	.000	.008	.008
N	17	17	17	17
**. Correlation is significant at the 0.01 level (2-tailed).

 The correlation matrix shows interdependence among the variables (Chatterjee & Hadi, 2015). GDP has a negative significant relation with inflation and exchange rate. The correlation between GDP and cereal export is positive implying GDP and export of cereals move in the same direction.  Inflation has a positive correlation with exchange while a negative correlation with cereal export. Exchange rate has an inverse relation with cereal export.

4.3 Regression analysis

Effect of cereal export on GDP of Australia

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.979a	.958	.955	33697.84848
a. Predictors: (Constant), Cereal_export

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	383830887170.293	1	383830887170.293	338.015	.000b
Residual	17033174879.770	15	1135544991.985
Total	400864062050.063	16
a. Dependent Variable: GDP
b. Predictors: (Constant), Cereal_export

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	764266.876	19387.210		39.421	.000
Cereal_export	5547.725	301.750	.979	18.385	.000
a. Dependent Variable: GDP

  From the regression result, the value of R square is obtained as 0.958. The high value of R square implies a high degree of association indicating a good fitted model. The slope coefficient for cereal export is positive. This means export of cereals has a positive effect on GDP of Australia. p value for the coefficient is 0.000.  Probability vale of coefficient less than significance level of 0.05 implies rejection of null hypothesis indicating no significant relation between cereal export and GDP. Cereal export is therefore a positive significant determinant of GDP of Australia.

Effect of inflation on exchange rate of Australian dollar

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.426a	.182	.127	.26694
a. Predictors: (Constant), Inflation

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	.237	1	.237	3.330	.088b
Residual	1.069	15	.071
Total	1.306	16
a. Dependent Variable: Exchange_rate
b. Predictors: (Constant), Inflation

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	.980	.201		4.874	.000
Inflation	.125	.068	.426	1.825	.088
a. Dependent Variable: Exchange_rate

From the regression result, the value of R square is obtained as 0.182. The small value of R square implies a weak association indicating a bad fitted model. The slope coefficient for inflation is positive. This means inflation has a positive effect on GDP of Australia. p value for the coefficient is 0.088.  Probability vale of coefficient greater than significance level of 0.05 implies acceptance of null hypothesis indicating no significant relation between inflation and exchange rate.

Effect of inflation on cereal export of Australia

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.623a	.388	.347	22.55298
a. Predictors: (Constant), Inflation

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	4841.700	1	4841.700	9.519	.008b
Residual	7629.550	15	508.637
Total	12471.251	16
a. Dependent Variable: Cereal_export
b. Predictors: (Constant), Inflation

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	107.871	16.985		6.351	.000
Inflation	-17.823	5.777	-.623	-3.085	.008
a. Dependent Variable: Cereal_export

From the regression result, the value of R square is obtained as 0.388. The relatively small value of R square implies a weak relation between inflation and cereal export indicating a good fitted model.  Inflation can explain only 38 percent variation in Cereal export. The slope coefficient for inflation is positive. This means inflation has an adverse effect on cereals export of Australia. p value for the coefficient is 0.008.  Probability vale of coefficient less than significance level of 0.05 implies rejection of null hypothesis indicating no significant relation between cereal export and inflation. Inflation is therefore a negative significant determinant of cereal export of Australia.

5. Discussion

Hypothesis 1: Cereal export is significantly related with GDP of Australia

             The first hypothesis proposes presence of a significant relation between cereal export and Gross Domestic Product of Australia. Data of last 17 years reveals a rising trend for both GDP and cereal export. From the correlation result, a positive correlation is found to exist between GDP and cereal export. The result of correlation is further supported by the result of regression. The regression of GDP on export of cereal indicates a positively significant relation between GDP and cereal export. This implies as cereal export increases GDP of Australia increases and vice versa. Primary export industry thus has a positive influence on economic growth of Australia. This supports the result of previous studies (Kalaitzi, 2013).

Hypothesis 2: Inflation rate is significantly related with exchange rate of Australia

            The second hypothesis is designed examine a statistically significant relation between exchange rate and rate of inflation. Exchange rate measures the value of Australian dollar relative to US dollar (Goodwin et al., 2015). Correlation between exchange rate and inflation suggest a positive association between exchange rate and inflation. The regression though finds a positive relation between exchange rate and inflation but this the relation is not statistically valid. Regression result shows acceptance of null hypothesis asserting no significant relation between inflation and exchange. This contradicts results of some previous literature (Arslaner et al., 2014). The relation of inflation with exchange rate hence remains undetermined.  

Hypothesis 3: Inflation rate is significantly related with cereal export of Australia

            The final hypothesis asserts a significant relation between cereal export and inflation. Inflation shows an overall declining trend while cereal export increases overtime. Analysis of correlation reveals an inverse relation between inflation and cereal export. Estimated regression result also shows a negative significant relation of inflation with cereal export. Increase in domestic price level thus has a negative influence on cereal export. Lower inflation leads to higher export of cereals leading to a higher GDP. This implies primary export of Australia is adversely influenced by price level. This is possible when ongoing price rise increases cost of production leading to a reduction in production and export (Agénor & Montiel, 2015). This indicates inflation in Australia is mostly caused from rising production cost.

6. Conclusion

6.1 Addressing the aims and research question

            The main objective of the research paper is to find how inflation influences cereal and cereal preparation export of Australia. The research questions are framed in accordance to the research aims.

            The first question is how cereal export affects Australian economy. To find an overall effect gross domestic product of Australia is taken as an indicator. The paper finds a positive significant association between GDP and cereal export. That means higher cereal export leads to a higher GDP for Australia.

            The second question is how inflation affects exchange rate of Australia. The analysis shows a positive relation between inflation and exchange rate. That means a higher domestic price level means a larger sum of Australian dollar needs to be exchanged for one unit of US dollar. This in turn means depreciation of Australian dollar. However, neither correlation nor regression result is statistically significant. Therefore, no valid relation can be established between inflation and exchange rate.

            The third question is the most vital. It tries to find how inflation influence cereal export of Australia. A negative significant relation is found between inflation and cereal export. Higher inflation thus creates an unfavorable condition for cereal export. Lower inflation on the other hand increases export of cereal enhancing GDP and economic growth.

6.2 Limitation

            Limitation of the research paper lies in consideration of a relatively small sample period, analysis of limited number of variables and such other. The paper considers a sample period from 2000 onwards. Sample data has been analyzed only for 17 years. Extending the time might provide a better result. Secondly, cereal export might depend on a number of other factors like domestic demand, weather and other necessary harvesting condition. These attributes can be included to extend the research further.

6.3 Recommendation

            The study finds a positive influence of cereal export on GDP of Australia. Therefore, cereal export should be encouraged to increase improve GDP and economic growth. Support should be given to the industry to increase production and export availability. Advanced technology should be used to increase production of cereals. Inflation is found to have an adverse effect on cereal export. As cereal export has direct relation with GDP inflation also adversely affects GDP. Measures therefore should be taken to stabilize price. Farmers need to optimize cost of harvesting so that inflation can have a limited effect on production and export.

Reference list

Abdurehman, A. A., & Hacilar, S. (2016). The Relationship between Exchange Rate and Inflation: An Empirical Study of Turkey. International Journal of Economics and Financial Issues, 6(4).

Agénor, P. R., & Montiel, P. J. (2015). Development Macroeconomics Fourth edition. Economics Books.

Ahdi N. Ajmi & Goodness C. Aye & Mehmet Balcilar & Rangan Gupta,( 2013). Causality between Exports and Economic Growth in South Africa: Evidence from Linear and Nonlinear Tests, Working Papers 201339, University of Pretoria, Department of Economics.

Arslaner, F., Karaman, D., Arslaner, N., & Kal, S. H. (2014). The Relationship between Inflation Targeting and Exchange Rate Pass-Through in Turkey with a Model Averaging Approach. Central Bank of the Republic of Turkey Working Paper, (14/6).

Auer, R. A. (2015). Exchange Rate Pass?Through, Domestic Competition, and Inflation: Evidence from the 2005–08 Revaluation of the Renminbi. Journal of Money, Credit and Banking, 47(8), 1617-1650.

Belloumi, M. (2014). The relationship between trade, FDI and economic growth in Tunisia: An application of the autoregressive distributed lag model. Economic Systems, 38(2), 269-287.

Bussière, M., Delle Chiaie, S., & Peltonen, T. A. (2014). Exchange rate pass-through in the global economy: the role of emerging market economies. IMF Economic Review, 62(1), 146-178.

Chatterjee, S., & Hadi, A. S. (2015). Regression analysis by example. John Wiley & Sons.

Ghosh, A. R., Ostry, J. D., & Chamon, M. (2016). Two targets, two instruments: monetary and exchange rate policies in emerging market economies. Journal of International Money and Finance, 60, 172-196.

Gilpin, R. (2016). The political economy of international relations. Princeton University Press.

Goodwin, N., Harris, J. M., Nelson, J. A., Roach, B., & Torras, M. (2015). Macroeconomics in context. Routledge.

He, X., Brouthers, K. D., & Filatotchev, I. (2018). Market orientation and export performance: The moderation of channel and institutional distance. International Marketing Review, 35(2), 258-279.

Hox, J. J., Moerbeek, M., & van de Schoot, R. (2017). Multilevel analysis: Techniques and applications. Routledge.

Kalaitzi, A. (2013). Exports and economic growth in the United Arab Emirates. In Submitted to: RIBM Doctoral Symposium. Manchester Metropolitan University Business School.

MacDonald, G. K., Brauman, K. A., Sun, S., Carlson, K. M., Cassidy, E. S., Gerber, J. S., & West, P. C. (2015). Rethinking agricultural trade relationships in an era of globalization. BioScience, 65(3), 275-289.

Mallik, G., & Chowdhury, A. (2011). Effect of inflation uncertainty, output uncertainty and oil price on inflation and growth in Australia. Journal of Economic Studies, 38(4), 414-429.

Mansfield, E. D., & Reinhardt, E. (2015). International institutions and the volatility of international trade. In The Political Economy Of International Trade (pp. 65-96).

Ozkan, F. (2013). Comparing the forecasting performance of neural network and purchasing power parity: The case of Turkey. Economic Modelling, 31, 752-758.

Shihab, R. A., Soufan, T., & Abdul-Khaliq, S. (2014). The causal relationship between exports and economic growth in Jordan. International Journal of Business and Social Science, 5(3).

Vahlne, J. E., & Johanson, J. (2017). The internationalization process of the firm—a model of knowledge development and increasing foreign market commitments. In International Business (pp. 145-154). Routledge.