Analyzing The Impact Of Income, Inflation And Tariff Rate On Schmeckt Gut’s New Product Demand: A Regression Analysis

The Influence of Income, Inflation and Tariff Rate on Demand

According to the principle of economics, the demand for a product depends on a lot of direct and indirect factors. It is important for a company like Schmeckt Gut to understand and forecast the demand for their new product. The income of the consumers, inflation and the tariff rate has a crucial influence on the demand of the product. The objective of this report is to understand the influence of the variables such as the change in the income, inflation and the tariff rate.

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The study uses the data of the research department of the company and uses regression analysis to synthesise the data in order to get an insight regarding the demand for the new product of the company.

Different projections regarding the variable

Scenario 1- 5% increase in income, 10% tariff rate and 5% inflation

This scenario is possible as high-income growth of 5% with the presence of a 10% tariff rate can change the demand for the product in the domestic market. In this case, the demand curve shifts to the right and increases the price of the product. This in turn, also increases the inflation level in the economy. Boserup (2017) stated that this is a common phenomenon under the boom phase of the business cycle to have a higher inflation level corresponding to a higher income of the consumer. In addition to that, the increased consumption corresponding to the increased income can also increase the overall output of the economy as per the theory of aggregate demand.

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In both the ways, the price of the product has the opportunity to go up pushing a lot of pressure on the inflation of the economy (Pigou, 2017). Furthermore, this scenario also has a high tariff rate which can be considered as a tax for the importer. Laffer curve shows that, with the increase in the tax rate, the revenue of the government increases as people prefer to buy from outside with the tariff rate applied. However, after a certain point, the consumers prefer to buy the products from the domestic market as the tariff rate increase further. Lastly, as per the theory of Phillips as the income increases the number of unemployed people decreases that impacts on the inflation rate and the number of stores in the market.

                                                               The Phillips curve

Scenario 2- 1% increase in income, 7.5% tariff rate and 3% inflation

This projection of this scenario is also matching as low-income growth, in this case, has contributed to the increase in inflation (Brander & Spencer, 2015). Now the despite the low-income increase, the inflation increase by 3% due to the fact that, tariff rate is moderately high. Consumers of the market are discouraged to pay the tariff and bring the product from outside. Thus, the domestic demand curve for the product shifts to the right and increases the price and hence the inflation of the economy. In addition to that, higher inflation can lower the unemployment rate leading to a further push in inflation. Therefore, 1% increase in income can create a 3% inflation rate if the tariff or the tax rate is moderately high (Leontief, 2016). The increased aggregate demand of the domestic market due to the increase in income and the tariff also increases the output that necessitates the number of stores to increase in the market.

Different Projections Regarding the Variables

                                                                   The demand and supply curve

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

This scenario has a moderately high-income increase which has the potential to increase the inflation of the market through increased demand for the product. However, the tariff rate is low as well and according to the Laffer curve, consumers would prefer buying the product  from the outside paying the tariff rate (McFadden, 2017). Therefore, the increase in income would not be able to contribute significantly to the growth of the aggregate demand of the economy.

However, according to the Phillips curve, the increased income means more and more consumers are employed and hence higher the inflation rate. In addition to that, a part of the consumers would be willing to buy the product from the domestic market despite the tariff and hence that would shift the demand curve for the product slightly to the right increasing the price level and hence the inflation (Fontagné et al. 2015).

                                              The aggregate demand and supply curve

Scenario 4- 7% increase in income, 0% tariff rate and 2% inflation

Income increase in this scenario is the highest, however; the inflation rate is still lower than other scenarios. This situation is also possible as there is a free trade that would allow the consumer to buy the product from the foreign market. One of the direct consequences of this could be a lower contribution to the aggregate demand of the economy (Chang & Li, 2018). The aggregate supply curve would remain the same and the aggregated demand would shift to the right only slightly increasing the inflation just by a little. Due to the lack of demand in the domestic market, the number of stores in the scenario can also be less.

                                                              The laffer curve

Impact of the different projections and the regression analysis

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.950868488

R Square

0.904150881

Adjusted R Square

0.880188601

Standard Error

0.072667887

Observations

21

ANOVA

df

SS

MS

F

Significance F

Regression

4

0.796999105

0.199249776

37.7322561

5.87E-08

Residual

16

0.08448995

0.005280622

Total

20

0.881489055

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

3.65625

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

Number of stores

0.034983162

0.017711161

1.975204351

0.06575708

-0.00256

0.072529

-0.00256

0.072529

Changes in the average income

2.36216E+11

2.1676E+11

1.089756719

0.29196162

-2.2E+11

6.96E+11

-2.2E+11

6.96E+11

Changes in tarriff

-0.541317108

0.097438961

-5.55544828

4.3483E-05

-0.74788

-0.33476

-0.74788

-0.33476

Inflation

-12432399665

11408417538

-1.089756719

0.29196162

-3.7E+10

1.18E+10

-3.7E+10

1.18E+10

This regression is a good fit which can be seen from the R square value which is 0.90. Now the analysis says that Changes in the average income is the most significant variable that influences the demand for the product. The coefficient of the income variable is very high and hence for a unit change in the variable, the demand changes by a huge amount. The p-value of the variable is also less than 0.5 that means the variable is significant (Manganaro, Lawal & Goodall, 2015). However, change in tariff does not have a significant impact on the demand in this scenario. The tariff is already very high and hence the change in tariff does not impact the demand for the product (Leamer & Stern, 2017). Lastly, the number of stores which has a coefficient of 0.03 has much less impact on the demand for the new product.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.950868488

R Square

0.904150881

Adjusted R Square

0.880188601

Standard Error

0.072667887

Observations

21

ANOVA

df

SS

MS

F

Significance F

Regression

4

0.796999105

0.199249776

37.73226

5.87E-08

Residual

16

0.08448995

0.005280622

Total

20

0.881489055

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

3.65625

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

Number of stores

0.034983162

0.017711161

1.975204351

0.065757

-0.00256

0.072529

-0.00256

0.072529

Changes in the average income

2.36216E+11

2.1676E+11

1.089756719

0.291962

-2.2E+11

6.96E+11

-2.2E+11

6.96E+11

Changes in tarriff

-0.541317108

0.097438961

-5.55544828

4.35E-05

-0.74788

-0.33476

-0.74788

-0.33476

Inflation

-12432399665

11408417538

-1.089756719

0.291962

-3.7E+10

1.18E+10

-3.7E+10

1.18E+10

Scenario 1- 5% Increase in Income, 10% Tariff Rate and 5% Inflation

This regression also has a good fit as the R squared value is very close to 0. In this case, also, the change in income has a good influence on the demand for the product (Polinsky, 2018). The coefficient suggests that, for a unit increase in the income, the demand increases a lot. The p-value of the variable is less than 0.5 and hence it is significant. It is also important to note that the inflation level also impacts the demand. Rising inflation reduces the demand for the product as the variable has a negative coefficient. The unemployment which is shown through the number of stores in the market shows that it has a minimal impact on the demand for the new product of the company (Schoenwitz et al. 2017).

Scenario 3

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.947127318

R Square

0.897050157

Adjusted R Square

0.871312697

Standard Error

0.075311503

Observations

21

ANOVA

df

SS

MS

F

Significance F

Regression

4

0.790739895

0.197684974

34.85387

1.03E-07

Residual

16

0.09074916

0.005671822

Total

20

0.881489055

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

3.658203125

3712577.415

9.85354E-07

0.999999

-7870309

7870316

-7870309

7870316

Number of stores

0.036663217

0.018361564

1.996737187

0.063158

-0.00226

0.075588

-0.00226

0.075588

Change in average income

-18037858586

3.93852E+11

-0.04579856

0.964038

-8.5E+11

8.17E+11

-8.5E+11

8.17E+11

Change in tariff

-1.107809849

0.201745426

-5.491127452

4.93E-05

-1.53549

-0.68013

-1.53549

-0.68013

Inflation

552179344.5

12056696583

0.04579856

0.964038

-2.5E+10

2.61E+10

-2.5E+10

2.61E+10

This regression analysis has an R square value of 0.89 which states that the model is a good fit. However, this situation has a different outcome as the income has a negative impact on the demand for the product in the domestic market (Deming, 2018). On the other hand, inflation has a positive impact on the demand for the product. That can be due to the relationship between unemployment and the inflation as shown by Phillips curve.

The p-value of the inflation variable is 0.04 which shows the variable is significant in determining the demand for the product. In this scenario, the change in tariff has a negative impact on the demand. That means the increasing tariff reduces the demand for the product. Lastly, the number of stores variable has a small impact on the value of demand (Pezzey & Toman, 2017). This can be due to the moderate amount of tariff which cannot restrict the domestic sellers from buying the product from the outside.  

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.837813612

R Square

0.701931649

Adjusted R Square

0.590507822

Standard Error

0.124320267

Observations

21

ANOVA

df

SS

MS

F

Significance F

Regression

4

0.618745066

0.154686266

13.34463

5.72E-05

Residual

17

0.262743989

0.015455529

Total

21

0.881489055

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

3.625

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

#NUM!

Number of stores

0.072022271

0.028367823

2.538872013

0.021189

0.012171

0.131873

0.012171

0.131873

Change in the average income

5050652636

25454932641

0.198415478

0.845073

-4.9E+10

5.88E+10

-4.9E+10

5.88E+10

Change in tariff

0

0

65535

#NUM!

0

0

0

0

inflation

-3607609026

18182094744

-0.198415478

0.845073

-4.2E+10

3.48E+10

-4.2E+10

3.48E+10

The R square value of this model 0.70 which shows that model is significantly good. It needs to be noted in this case that, 0% change in tariff has no impact on the demand for the product. However, an increase in income can increase the demand for the product (Shackle, 2017). However, the increase in demand due to the increase in income is proportionately less than the other scenario as free trade exists in this situation. The p-value of the change in income is 0.19 which is significant. The number of stores which signifies the employment level shows that the demand increases with the number of stores (Lundvall, 2017). The p-value of the number of store variable is also significant showing that, it has an important contribution towards determining the demand for the new product.

Therefore, each of the different situations has different outcomes. While income has a positive impact on the demand in one scenario, it has a negative impact on the demand in another (Sodeyfi, 2016). Therefore, this study presents different recommendations to the board member of the company based on different projections.

In this scenario, higher income has a positive impact on the demand for the product. Apart from that, the tariff is also very high. Therefore, it is recommended to the board member to use a higher price for the product. The consumers of the market have no other choice than buying the product from the domestic market as the tariff is high (Aslan & Kumar, 2016). Thus, a high price would increase the revenue of the company. Although the inflation will have a negative impact on the demand, it will be lower than the increase in demand due to the increase in income.

Scenario 2- 1% Increase in Income, 7.5% Tariff Rate and 3% Inflation

In this scenario, the change in income has a huge impact on the demand for the product just like the previous scenario. However, the relative change in income compared to the change in inflation is low and hence the demand would not be triggered (Battini, Bogataj & Choudhary, 2017). The company should use a competitive price for the new product under this scenario to attract the customers of the market. The tariff rate is little lower than the previous one and hence the lower price would allow the management to cut some of the customer’s bases of the foreign companies.

Here the impact of income increase on the demand for the product is actually negative. That means the increase in income can reduce the demand for the product. The product of the company here is an inferior good (Kumar, 2015). Therefore, management needs to note that and improve the quality of the new product. It is suggested to the board of the members to invest money on the promotion of the product so that it can make the customer aware about the product.

As the income growth, in this case, is high the impact on the demand for the new product is also high. With one unit change in the income, the demand increases by a large margin. However, free trade provides a great threat to the product of the company. Therefore, it is recommended to the management of the company to use a competitive price for the product. A price war with the rivals can also benefit the production of the company if the promotion of the product is done right (Belanger, O’Sullivan & Littlewood, 2018). The low price will also help the company to coup with the negative impacts of the inflation on the demand for the product.

Conclusion

Therefore, the demand for the product of Schmeckt Gut depends on a lot of variables. These variables have been incorporated into the model. The study presents four different scenarios based on the projection and the data provided by the research department of the company. According to the study, the change in income has the most significant impact on the demand for the new product of Schmeckt Gut. However, the magnitude and the type of impact on the demand depend upon the different projections of income, tariff and inflation rate. Inflation rate also has a significant impact on the demand for the product. However, whether the inflation impacts the demand negative or positively depends upon the income growth and the tariff rate on the product.

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