Brief Description
The Australian Chamber of Commerce is Australia's largest and most representative business association. And it presents the Australian peak council of business organizations & the authentic voice of Australian enterprise & industry. One of a number of responsibilities of ACCI is to publish Australian small enterprises’ business interests. In the interest’s analysis of a huge number of small enterprises, the most important part of the analysis is small enterprises’ interest when the economy during the peaks and troughs in an economic cycle. Small enterprises in the peak, GDP and economic growth rate rise and their costs of inputs rose. On the other hand, small enterprises’ revenue often decreases when there is a trough.
 
There are two main parts in the report, the report will analysis effects of global financial crisis on small enterprises based on real data of retails sales firstly, then the report will provide a consideration of medium term expectation for Australian small enterprises retails.
 
In order to explain effects of global financial crisis on Australian retail industries, the report investigated and analyzed a number of real data that was associated with retails. These variables includes retail turnover rates, interest rates, unemployment rates, consumer price index, consumer confidence index and dummy variables of the global financial crisis.
 
Interest rate is controlled by the RBA, and changing interest is the main method of monetary police. The government uses monetary police to influence the cash supply and demand in the market. Interest rate changing affects the cash supply and demand to influence business investment and consumption. Unemployment rate not only is the mark of current economy situation in the economic cycle, but it also reflects whole national residents’ income. Therefore, unemployment rate is a way to analyses the effects of GFC on retail sales. Consumer price index monthly variables reflect the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Thus, CPI is a main tool to understand the inflation rate and households real wages. Consumer confidence index is an indicator designed to measure consumer confidence, which could be understood as the degree of optimism on the state of the economy that consumers are expressing through their activities of savings and spending. Therefore, CCI could reflect directly consumers’ consumption and how retail industries were influenced by GFC. In the report, the dummy variable is used to mark off the effects of global financial crisis. When the economy during the GFC, the dummy variable equals one, if not, it equals zero. Retail turnover rate is one of many factors to evaluate performance of small enterprises, which is used to explain the effects of GFC. And the report uses below regression to explain retail turnover. Y is retail turnover; variables in the formulae are those factors that have effects on retail and were explained in the prior.
y=β₀+β₁x₁₊β₂x₂₊β₃x₃₊β₄D

Variables analysis

In the variable analysis, the report based on data monthly from January of 1991 to March of 2014, and which was collected from the website of Australian Bureau of Statistics, Reserve Bank of Australia and Bloomberg database. The report chooses and collects four independent variables and one dependent variable. In the report, the retail sales turnover contains Cafes, restaurants and takeaway food services. The four independent variables are interest rate, unemployment rate, Consumer Confidence Index and global financial crisis dummy variable. And the dependent variable is retail sales turnover with the unit of million dollars. In the variable analysis, the unit of interest rate and unemployment rate is percentage; consumer confidence index is a constant number; and one or zero presents the global financial crisis dummy variable.
The report used the Excel as main tool to analyses data was collected from website.
 
The global financial crisis can affect the retail sales turnover due to unemployment or the fear of the unemployment, people buy something just they need not they want. Retail sales turnover is look on as an economic indicator, because retail sales are one of significant component part of GDP.
 
The Global Financial Crisis from August 2007 is treated as the largest financial shock since the Great Depression (Bush, 2008),  and it cuased a full down global recession  in the global market around the world. The unemployment rate increased when the recession occurred which has the impact on the consumptions, also the retail sales turnover in Australia. Hence, in this report, a dummy variable was used to show whether there was a financial crises or not. From August 2007 to Now, the financial crisis exist, so D=1. And before August 2007, there is no financial crisis, so D=0.

Figure 1: charts of collected data in regression models
 
As we can see in the figure 1, there is a steady growth during these twenty years in retail sales turnover in Australia, thus an increase trend showing here. However, there is no obvious trend on the other four variables. There are fluctuant. The interest rates will be falling and the unemployment rate will be rising when the financial crisis appears. And the consumer confidence index fall largely. Thus the investments and consumptions will decline. So the retail sales turnover increases due to the inflation and bubble.

Methodology

We had used the Australia Bureau of Statistics and Reserve Bank of Australia to collect the data. We also used four variables to analyse and find the relationship between the retail turnovers. The four variables are interest rate, unemployment rate, Consumer Confidence index and dummy variable of global financial crisis.

We had used regression model to analyse. The basic regression is y= y=β₀+β₁x₁ where y is the predicted value β₀ is the intercept and β₁ is the slope.
 
The basic multiple regression model is:y=β₀+β₁x₁₊β₂x₂₊β₃x₃₊β₄D where y is the dependent Variable, β₀ is the intercept and β_1,2,3,4 is the coefficient for the independent variables.
 
Furthermore, the hypothesis was used to test whether it has an influence on the retail sale turnover during GFC.
H0: β₄ = 0, which means there is no effect
H1: β_{4 ≠ 0, which means there} is some effect.

Analysis Models

Test Model and Results
The explained variable shows the relationship between retail sales turnover, and the explained variable are interest rate, unemployment rate, Consumer Confidence index and dummy variable.
The table below shows the relation between the 4 factors.

	retail turnover	interest rate	unemployment rate	CCI
retail turnover	1
interest rate	-0.5764	1
unemployment rate	-0.7813	0.3663	1
CCI	0.1857	-0.4180	-0.3063	1

Table 1: The correlation between the variables
On the table 1, we can see the correlations of interest rate and unemployment rate pretty high. However, the correlation of the consumer confidence index is not high enough, and we also believe the consumer confidence affect the retail sales turnover.
Then, the multiple regression results are show at below.

Regression Statistics
Multiple R	0.9463
R Square	0.8955
Adjusted R Square	0.8939
Standard Error	223.4154
Observations	279
ANOVA
	df	SS	MS	F	Significance F
Regression	4	117155181.7	29288795.4	586.8	5.3877E-133
Residual	274	13676554.0	49914.4
Total	278	130831735.7

 

	Coefficients	Standard Error	t Stat	P-value
Intercept	2742.5913	228.2305	12.0168	5.2984E-27
interest rate	-72.8480	10.4062	-7.0004	1.9666E-11
unemployment rate	-144.9906	8.4168	-17.2264	1.4522E-45
CCI	1.2542	1.5736	0.7970	4.2612E-01
dummy	820.1435	40.3961	20.3025	1.4826E-56

Table 2: The regression results
Therefore, the final regression result is: RT=2742.59-72.85IR-144.99UR+1.25CCI+820.14D
Because the coefficients of interest rate and unemployment rate are negative, when the index increases, the return of retail will decrease. The CCI is positive, so when the consumer confidence increases, the retail turnover will also increase.
The high interest will decrease the willingness of consumer to consume and investor to invest, so when the interest is high, the retail turnovers will decrease. The high unemployment rate is usually during the economy recession and the income of household will decrease, as a result the returns of retail will also decrease. The increasing in Consumer Confidence Index showing the consumer are more likely to spend and less likely to save. Therefore, the turnovers of retail will increase and the effect of Consumer Confidence Index is positive.
 
The global financial crisis affects the whole world’s economy. When D=0, means no financial crisis. D=1, means during the financial crisis. Because the dummy variable is positive, the economic crisis has the goodinfluence on the turnover of retail sales which means it is caused by the inflation when the price of goods and raw materials increase despite the decline in consumer confidence. In our regression results, the turnover of retail sales is increase is due to the inflation is larger than the spending in the global economic crisis. The effect of global financial crisis may be larger than the total effect of others variable, since the global financial crisis will also influences the interest rate, employment rate and consumer confidence index while the three variables will also change the turnover of retail sales. In conclusion, we can state that the global financial crisis isvery influential on the turnover of retail sales.
 
Prediction Model and Results
Figure 2: the prediction regression model
We can find there is obviously trend in the retail turnover from the plot figure 1, so we can use line fitted method and forecasts the future values of retail turnovers.
To use the basic regression model to predict, we can get: y=8.2369x +570.23
Y is the retail sales and x is the time order. The R²=0.9391, so the result seems pretty good. From the figure 2, the blue straight line is the fitted line and uses it to fit in the origin retail turnover in Australia, so we can use it to predict the future retail turnover.
 

Regression Statistics
Multiple R	0.9691
R Square	0.9391
Adjusted R Square	0.9389
Standard Error	169.5457
Observations	279
ANOVA
	df		SS		MS		F		Significance F
Regression	1		122869161.7		122869161.7		4274.3412		2.113E-170
Residual	277		7962574.004		28745.7545
Total	278		130831735.7
		Coefficients		Standar Error		t Stat		P-value
Intercept		5.647234088		0.072027714		78.40363		2.6263E-187
time order		0.059671735		0.000459083		129.9804		8.628E-245

Table 3: The prediction regression model
The table 4 below shows the future value of retails sale in next 5 years from 2015 to 2019 when the x is correspond from 290 to 349.  The prediction retail turnover is 36050.90 million in 2015, 37237.01million in 2016, 38423.13 million in 2017, 39609.24 million in 2018 and 40795, 35 in 2019. The total five years value of retail turnover is 192115.6350 million dollar. From the Appendix 1, it shows the monthly future retail turnover.

Year	Predict Retail sales turnover (million $)
year 2015	36050.8998
year 2016	37237.0134
year 2017	38423.1270
year 2018	39609.2406
year 2019	40795.3542
Total five years value	192115.6350

Table 4: the predictions turnover
 

Limitation

We have some limitation in this report. First, we only have 279 data of retail turnover, so we may need more data to investigate to get more accurate results. Moreover, we only use 3 factors to analyses the report which may be too little and inadequate.
 

Recommendation

According to above analysis, the report presented clearly these factors (interest rate, CPI, unemployment rate and CCI) have influence on the sale turnover. However, the report did not find an effective method to explain the relationship between the sales turnover and each factor, because it is hard to distinguish the contribution of each factor to the changing of sales turnover. Meanwhile, the report also fails to provide respectively the number of sales turnover changing because of these factors. Therefore, the report sum up all effects of these factors together.

Conclusion

As the professional analysts who had been appointed by the Australian Chamber of Commerce. The duty of this organization is to protect and on behalf of the small enterprises. Peaks and troughs are patterns of price action experienced over the business economic cycle, that are particular concerned by small enterprises. Boom often refer to the increase of the costs of raw material, and during troughs, the revenue is often decrease. The problem we need to think at is the effect of global financial crisis, how to quantified the crisis and what is it mean in the near future? Being the professional analysts, we solve two problems in the report: the result of GFC on retail sales and predict the future value of the four variables we had chosen in the next five years. The four variables are interest rate, unemployment rate, Consumer Confidence Index and global financial crisis dummy variable
 
To investigate the problems, the report selects 280 monthly data from the Australian Bureau of Statistics from January 1991 to March 2014.
The report illustrate the effect of GFC on retail sales turnover is not bad, because the retail turnover is increased by 820.1435 million.Due to the GFC is not only affect the retail sales, but also the other economic factors, including interest rates, unemployment rates, Consumer Confidence Index. Therefore, the effect may larger than the total effect. Furthermore, the line charts for 3 variables shows that GFC has did contribution on the trend variation. Therefore, in conclusion, we can state that the GFC have good influence on turnovers of retail sales.
Base on prognosis in five years, the prediction model of the retail sale turnover, the retail trade sector are respectively about 36050.8998 million dollars, 37237.0134 million dollars, 38423.1270 million dollars, 39609.2406 million dollars, 40795.3542 million dollars. To sum up,the medium term prognosis for thetotal retail sales turnover is approximate 192115.635 million dollars.

Reference

Bush (2008).President Bush's Address to Nation.The New York Times, September 24, 2008.
Consumer condifenceindex, WIKIPEDIA, http://en.wikipedia.org/wiki/Consumer_confidence_index
WHO-WE- ARE, The Australian Chamber Of Commerce And Industry,http://www.acci.asn.au/Who-We-Are
Consumer price index, WIKIPEDIA, http://en.wikipedia.org/wiki/Consumer_price_index

Appendix

x	retail turnover
290	2958.9387
291	2967.1756
292	2975.4125
293	2983.6494
294	2991.8863
295	3000.1232
296	3008.3601
297	3016.5970
298	3024.8339
299	3033.0708
300	3041.3077
301	3049.5446
year 2015	36050.8998
302	3057.7815
303	3066.0184
304	3074.2553
305	3082.4922
306	3090.7291
307	3098.9660
308	3107.2029
309	3115.4398
310	3123.6767
311	3131.9136
312	3140.1505
313	3148.3874
year 2016	37237.0134
314	3156.6243
315	3164.8612
316	3173.0981
317	3181.3350
318	3189.5719
319	3197.8088
320	3206.0457
321	3214.2826
322	3222.5195
323	3230.7564
324	3238.9933
325	3247.2302
year 2017	38423.1270
326	3255.4671
327	3263.7040
328	3271.9409
329	3280.1778
330	3288.4147
331	3296.6516
332	3304.8885
333	3313.1254
334	3321.3623
335	3329.5992
336	3337.8361
337	3346.0730
year 2018	39609.2406
338	3354.3099
339	3362.5468
340	3370.7837
341	3379.0206
342	3387.2575
343	3395.4944
344	3403.7313
345	3411.9682
346	3420.2051
347	3428.4420
348	3436.6789
349	3444.9158
year 2019	40795.3542

Table 5: The monthly prediction values of retail sales turnovers