Interpretation And Forecasting Of Demand For A New Product Using Economic Concepts | Schmeckt Gut Case Study

Methods

Schmeckt Gut is a company that is going to launch a new product in the market. Thus, the research department of the company has collected data and information about different variables of the market that can help in the determination and the forecasting of the demand for the new product. This study carries out a regression analysis on the collected data to get an insight regarding the forecasted demand for the product.

A multiple linear regression has been done using the collected data of the research department of Schmeckt Gut. The results of the linear regression have been interpreted in the paper to present a clear picture of the impacts of the variables on the demand for the new product.

Matching of different projections

Income, inflation, unemployment, and tariff which are a tax, in this case, are all related to each other in the macroeconomic platform. Therefore, some of the projections regarding the increase in the value of the variable can be matched using economic theories and concepts.

Scenario 1: 7% increase in income, 0% tariff and 2% inflation

Income of the consumers can directly influence the inflation level of the economy. Sodeyfi (2016) pointed out that, income increases the purchasing power of the consumers of the market that in turns shifts the demand curve for the goods and the service towards the right. If the single product is considered the demand curve for that product will shift to the right and increase the price. Apart from that, according to the principle, the rise in income can also increase the aggregate demand for all the goods and services of the economy (Shackle, 2017). This 7% increase in income of the consumer can shift the aggregate demand to the right side leading to a higher overall price level and output. However, the tariff rate which is the tax rate on imported goods can reduce the impact of an increase in income on the inflation of the economy (Flammer, 2015). The consumer may use their increased income to buy goods from the foreign economy that will hardly influence the inflation level of the domestic economy. The Laffer curve which depicts the relationship between the tax rate and the tax revenue shows that at a lower level the tariff is not restrictive. In addition to that, lower employment would be created in the domestic economy which further explains the lower inflation level in the domestic economy in line with the Phillips curve (Schoenwitz, Potter, Gosling & Naim, 2017).

Scenario 2 – 3% increase in income, 5% tariff rate and 2% inflation

This projection related to the increase of the variable can also be matched. In this case, the increase in income is much lower than in the previous scenario. However, it has generated the same amount of inflation in the economy. The 3% increase in income is matched with the 2% inflation as the tariff rate is moderately high at 5% (Shafritz, Ott & Jang, 2015). That means the consumers of the domestic market has some degree of restriction to buy the goods from the foreign market. However, the tariff rate is not that high to fully restrict the consumers of the market. laffer curve shows that the tax revenue increases with tax and decreases after a certain point. Therefore, the 3% increase in income is a perfect match and a possibility for the 2% inflation in the economy (Polinsky, 2018). In terms of the theory of aggregate demand, the income of the consumer increases the demand for all goods and services that further amplifies the inflation rate in the economy. In this case, the increase in income also denotes the number of consumers with increased income. Lastly, the Phillips curve shows the relationship between the inflation rate and the unemployment rate of the economy. In this case, the unemployment will still be very high due to the low tariff on the product which will shift some of the demand from the domestic to the foreign market. Therefore the number of stores under this projection will be low (Pigou, 2017).

Discussion

Scenario 3- 1% income increase, 7.5% tariff, 3% inflation

This scenario has a very low increase in the income of consumers. Despite this fact, the inflation is the more than the previous cases. Generally, the aggregate demand and supply schedule shows that with the increase in the overall price the inflation level of the economy surges (Pezzey & Toman, 2017).  However, in this particular case, the existing tariff rate also needs to be taken into consideration. The tariff rate of 7.5% is very high compared to the previous scenario. According to the Laffer curve the higher the tax or the tariff rate, lesser the consumer will be willing to pay the tax. Therefore at this high tariff rate, the consumers of the market would shift their demand to the domestic market increasing the demand for domestic products (McFadden, 2017). Most of the income of the consumers would contribute towards the aggregate demand of the domestic market. Consequently, the inflation would shoot up more than the natural. Therefore, the projection of a 1% increase in the interest rate is thus perfectly matched with the 3% inflation in the economy. The shift of the consumption to the domestic market and the high inflation is also the evidence that the unemployment rate would be lower and hence the number of stores which denotes the employment rate in this study will increase (Manganaro, Lawal & Goodall, 2015).

Scenario 4- 5% increase income, 10% tariff and 5% inflation

This scenario is the perfect example of a closed market where the tariff rate is very high. The demand for the new product would be influenced by the change in the income in this scenario (Lundvall, 2017). The projections are matching due to the fact that, higher inflation matches with higher income of the consumer. In this case, the aggregate demand of the economy would be very responsive to the change in the income. The consumers of the market would prefer buying the products from the domestic market and hence the number of stores and the inflation would rise (José Ganuza, Gomez & Robles, 2016). The high-income increase of the consumer would directly impact the demand for the single product and the price would go up. That means under this situation, the company has a great opportunity to use higher prices to improve the revenue of the company (Leontief, 2016). However, the higher prices would have a contribution to the inflation level. Therefore, the projections regarding the variable are matching and justified by the theories of aggregate demand and the Laffer curve.

Impact of different prediction on the demand for the product

Annual average demand for energy bars per person	Average income per person	Tariff rate on imports of energy bars	Number of stores	Changes in the average income	Changes in tariff	Inflation
For Scenario 1
106	15500	5	15	10850	0.00	15190
90	15810	5	15	11067	0.00	15493.8
93	16395	5	15	11476.5	0.00	16067.1
92	16887	5	15	11820.9	0.00	16549.26
91	17495	5	15	12246.5	0.00	17145.1
110	18282	5	16	12797.4	0.00	17916.36
109	19013	5	16	13309.1	0.00	18632.74
122	19508	5	16	13655.6	0.00	19117.84
82	19898	10	16	13928.6	0.00	19500.04
84	20276	10	16	14193.2	0.00	19870.48
102	20702	10	17	14491.4	0.00	20287.96
92	21550	10	17	15085	0.00	21119
115	22197	10	20	15537.9	0.00	21753.06
112	22330	10	20	15631	0.00	21883.4
109	22754	10	20	15927.8	0.00	22298.92
148	23619	8	20	16533.3	0.00	23146.62
143	23855	8	20	16698.5	0.00	23377.9
139	24452	8	20	17116.4	0.00	23962.96
158	24941	8	23	17458.7	0.00	24442.18
142	25514	8	23	17859.8	0.00	25003.72
158	25948	8	23	18163.6	0.00	25429.04
Scenario 2
106	15500	5	15	465	0.25	15190
90	15810	5	15	474.3	0.25	15493.8
93	16395	5	15	491.85	0.25	16067.1
92	16887	5	15	506.61	0.25	16549.26
91	17495	5	15	524.85	0.25	17145.1
110	18282	5	16	548.46	0.25	17916.36
109	19013	5	16	570.39	0.25	18632.74
122	19508	5	16	585.24	0.25	19117.84
82	19898	10	16	596.94	0.50	19500.04
84	20276	10	16	608.28	0.50	19870.48
102	20702	10	17	621.06	0.50	20287.96
92	21550	10	17	646.5	0.50	21119
115	22197	10	20	665.91	0.50	21753.06
112	22330	10	20	669.9	0.50	21883.4
109	22754	10	20	682.62	0.50	22298.92
148	23619	8	20	708.57	0.38	23146.62
143	23855	8	20	715.65	0.38	23377.9
139	24452	8	20	733.56	0.38	23962.96
158	24941	8	23	748.23	0.38	24442.18
142	25514	8	23	765.42	0.38	25003.72
158	25948	8	23	778.44	0.38	25429.04
Scenario 3
106	15500	5	15	155	0.38	15035
90	15810	5	15	158.1	0.38	15335.7
93	16395	5	15	163.95	0.38	15903.15
92	16887	5	15	168.87	0.38	16380.39
91	17495	5	15	174.95	0.38	16970.15
110	18282	5	16	182.82	0.38	17733.54
109	19013	5	16	190.13	0.38	18442.61
122	19508	5	16	195.08	0.38	18922.76
82	19898	10	16	198.98	0.75	19301.06
84	20276	10	16	202.76	0.75	19667.72
102	20702	10	17	207.02	0.75	20080.94
92	21550	10	17	215.5	0.75	20903.5
115	22197	10	20	221.97	0.75	21531.09
112	22330	10	20	223.3	0.75	21660.1
109	22754	10	20	227.54	0.75	22071.38
148	23619	8	20	236.19	0.56	22910.43
143	23855	8	20	238.55	0.56	23139.35
139	24452	8	20	244.52	0.56	23718.44
158	24941	8	23	249.41	0.56	24192.77
142	25514	8	23	255.14	0.56	24748.58
158	25948	8	23	259.48	0.56	25169.56
Scenario 4
106	15500	5	15	775	0.50	14725
90	15810	5	15	791	0.50	15020
93	16395	5	15	820	0.50	15575
92	16887	5	15	844	0.50	16043
91	17495	5	15	875	0.50	16620
110	18282	5	16	914	0.50	17368
109	19013	5	16	951	0.50	18062
122	19508	5	16	975	0.50	18533
82	19898	10	16	995	1.00	18903
84	20276	10	16	1014	1.00	19262
102	20702	10	17	1035	1.00	19667
92	21550	10	17	1078	1.00	20473
115	22197	10	20	1110	1.00	21087
112	22330	10	20	1117	1.00	21214
109	22754	10	20	1138	1.00	21616
148	23619	8	20	1181	0.75	22438
143	23855	8	20	1193	0.75	22662
139	24452	8	20	1223	0.75	23229
158	24941	8	23	1247	0.75	23694
142	25514	8	23	1276	0.75	24238
158	25948	8	23	1297	0.75	24651

Table 1: the impacts of the variables on the demand for the product

(Source: Developed by the learner)

Scenario 1: 7% increase in income, 0% tariff and 2% inflation

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.877304
R Square	0.769663
Adjusted R Square	0.587078
Standard Error	13.17559
Observations	21
ANOVA
	df	SS	MS	F	Significance F
Regression	6	9281.031	1546.839	13.36583	4.37E-05
Residual	16	2777.54	173.5963
Total	22	12058.57
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	5824	4.04E+08	1.44E-05	0.999989	-8.6E+08	8.56E+08	-8.6E+08	8.56E+08
Average income per person	-1.9E+12	2.65E+12	-0.72894	0.476573	-7.6E+12	3.69E+12	-7.6E+12	3.69E+12
Tariff rate on imports of energy bars	-655.367	367.4509	-1.78355	0.093474	-1434.33	123.5939	-1434.33	123.5939
Number of stores	2.232178	4.390735	0.508384	0.618122	-7.07576	11.54012	-7.07576	11.54012
Changes in the average income	0	0	65535	#NUM!	0	0	0	0
Changes in tariff	0	0	65535	#NUM!	0	0	0	0
Inflation	1.97E+12	2.71E+12	0.728942	0.476573	-3.8E+12	7.71E+12	-3.8E+12	7.71E+12

This regression analysis has an R square value of 0.76 which indicates that the analysis is a good fit.  According to the result of the analysis, higher income negatively impacts the demand for the new product (Leamer & Stern, 2017). The p-value of the variable is less than 0.5 making it significant. This can be due to the presence of free trade in this scenario. Increased income can easily be spent on the goods and services of the foreign economy. Another significant variable that determines the demand for the product of the company is the inflation of the economy. Inflation has a positive impact on the demand for the product (Kumar, 2015). The p-value for this variable is less than 0.5 indicates that the variable is significant in determining the demand for the product of the company.

Matching of different projections

Scenario 2 – 3% increase in income, 5% tariff rate and 2% inflation

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.956846
R Square	0.915555
Adjusted R Square	0.820739
Standard Error	0.070445
Observations	21
ANOVA
	df	SS	MS	F	Significance F
Regression	6	0.807051	0.134509	32.52589	1.92E-07
Residual	15	0.074438	0.004963
Total	21	0.881489
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	3.4375	#NUM!	#NUM!	#NUM!	#NUM!	#NUM!	#NUM!	#NUM!
Average income per person	-3.5E+10	1.94E+10	-1.81325	0.08985	-7.7E+10	6.18E+09	-7.7E+10	6.18E+09
Tariff rate on imports of energy bars	-0.05847	0.009741	-6.00292	2.42E-05	-0.07923	-0.03771	-0.07923	-0.03771
Number of stores	0.030637	0.01749	1.751743	0.100231	-0.00664	0.067916	-0.00664	0.067916
Changes in the average income	3.47E+11	3.13E+11	1.109101	0.284852	-3.2E+11	1.01E+12	-3.2E+11	1.01E+12
Changes in tarriff	0	0	65535	#NUM!	0	0	0	0
Inflation	1.88E+10	1.7E+10	1.108792	0.284981	-1.7E+10	5.51E+10	-1.7E+10	5.51E+10

This regression has a good foot as the R square value is pretty much high. For this scenario also the income growth has a negative impact on the demand for the product (Gu, 2016). The tariff rate is still low and hence the growth income would mainly be spent on the products of the foreign market. The p-value of the variable is 0.1 which shows that the chance for the random error is very low. It is important to note that, the increase in tariff in this scenario has an insignificant impact on the demand for the product. This can be explained through the Laffer curve as the increasing tax reduces the tax revenue. Inflation in this case also has the potential to influence the demand for the product by a large extent (Fontagné, Orefice, Piermartini & Rocha, 2015). The coefficient of the variable is high shows that that one unit increase in inflation can increase the demand for the product.

Scenario 3- 1% income increase, 7.5% tariff, 3% inflation

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.951797
R Square	0.905918
Adjusted R Square	0.757397
Standard Error	0.071995
Observations	21
ANOVA
	df	SS	MS	F	Significance F
Regression	6	0.798557	0.133093	38.51608	6.45E-08
Residual	16	0.082932	0.005183
Total	22	0.881489
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	3.625	7268845	4.99E-07	1	-1.5E+07	15409266	-1.5E+07	15409266
Average income per person	1.8E+10	1.45E+10	-1.22898	0.236849	-4.8E+10	1.29E+10	-4.8E+10	1.29E+10
Tariff rate on imports of energy bars	-0.05565	0.009594	-5.80095	2.71E-05	-0.07599	-0.03532	-0.07599	-0.03532
Number of stores	0.030887	0.018112	1.705328	0.107468	-0.00751	0.069283	-0.00751	0.069283
Change in average income	0	0	65535	#NUM!	0	0	0	0
Change in tariff	0	0	65535	#NUM!	0	0	0	0
Inflation	1.81E+10	1.47E+10	1.22898	0.236849	-1.3E+10	4.94E+10	-1.3E+10	4.94E+10

With 0.9 R squared value, it shows that the regression for this scenario is a good fit. This regression analysis shows that the demand for the product increases with the increase in the income of the consumer (Deming, 2018). This can be due to the high tariff of this scenario. The consumers are bound to spend the income on the domestic product. Apart from that, inflation like the other scenarios has influence over the demand for the product (Chang & Li, 2018).

Scenario 4- 5% increase income, 10% tariff and 5% inflation

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.959416
R Square	0.92048
Adjusted R Square	0.7756
Standard Error	7.741534
Observations	21
ANOVA
	df	SS	MS	F	Significance F
Regression	6	11099.67	1849.945	46.30161	1.93E-08
Residual	16	958.9015	59.93134
Total	22	12058.57
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-8	#NUM!	#NUM!	#NUM!	#NUM!	#NUM!	#NUM!	#NUM!
Average income per person	1.8E+12	1.55E+12	-1.15867	0.263591	-5.1E+12	1.49E+12	-5.1E+12	1.49E+12
Tariff rate on imports of energy bars	-6.48864	1.03164	-6.28964	1.08E-05	-8.67562	-4.30166	-8.67562	-4.30166
Number of stores	3.47879	1.947568	1.786222	0.093026	-0.64987	7.607451	-0.64987	7.607451
Change in average income	0	0	65535	#NUM!	0	0	0	0
Change in tariff	0	0	65535	#NUM!	0	0	0	0
Inflation	1.84E+12	1.59E+12	1.158675	0.263591	-1.5E+12	5.2E+12	-1.5E+12	5.2E+12

The goodness of fit of this regression analysis is good as the r square value is 0.92. Income is the most significant variable that influences the demand for the product. The tariff is the highest in this scenario and hence most of the increase in the income of the consumer contributes to the inflation through the aggravated aggregate demand (Brander & Spencer, 2015).

Scenario 1: 7% increase in income, 0% tariff and 2% inflation

Income has a negative impact on the demand for the product as it is an inferior good in this market. Therefore the board of members is recommended to use a competitive pricing for the product.

Scenario 2 – 3% increase in income, 5% tariff rate and 2% inflation

The income growth in this scenario has a negative impact due to the presence of low tariff. However, an organisation can use a price little more than competitive price to improve the revenue of the organisation.

Scenario 3- 1% income increase, 7.5% tariff, 3% inflation

The tariff is very high and the income growth is slow. The organisation can use a premium pricing for the product as high tariff will compel the consumers to buy from the domestic market.

Scenario 4- 5% increase income, 10% tariff and 5% inflation

This scenario is the best in terms of improving the revenue of the company. The company needs to spend a high amount on the promotion so that it can attract most of the customers towards its product.

Conclusions

Therefore, this paper presents the regression analysis and the results related to the launch of the new product of the company. The projections have different impacts on the demand for the product. The study also furnishes recommendations to the board members based on different projections.

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