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Theoretical Framework

Discuss about the Humanism Challenge Materialism in Economics.

One of the major characteristics of economic variables is that they impact and influences other variables of economics. One such causal relationship can be seen in the field of consumption and supply-demand as well. The objective of this paper is to analyze causal relationship between different types of variables in case of Kuwait. Kuwait imports a lot of products from different countries of the world. One of the most important imported products of the country is bread (Cuomo et al. 2015). The import of bread is measured in terms of quintal per year. There are two of the variables that influence the import demand of bread in the country of Kuwait. These include the prices of bread and the income level of the customers of the market (Leuven and Sianesi, 2018). This is due to the fact that as the price of bread raises the customers of the markets demands less amount of bread and hence the import demand goes down. On the other hand, as the income of the customer of the market rises, the demand for the bread increases as customers prefers to consume more with the increase in income (Klamer, 2018). However, the impact of the income variable on the import demand of bread becomes negative after the income level of the customer reaches a definite point. After that, the product, bread, becomes an inferior good to the customers of the market. The study of the paper will apply economic theories related to the causal relationship provided above and test with statistical tools, the reliability of the hypothesis or the claim. Apart from that, this study is also going to trace the implication that the chosen variables have as well.

According to the principle of economics, the consumption of any good depends on the income of the customers of the market. This principle of economics suggests that at the level of no income the customer still consumes an amount of the product. Apart from as the income starts growing the demand also starts increasing (Stiglitz and Rosengard, 2015). However, it also needs to be noted that at the low level of income the consumption is more than the income. Therefore, this can be inferred that at a low level of income of the consumers of the economy the import demand for the bread can be proportionately more than that of income level (Pheby, 2015). The consumption equation is as follows:

Methodology

C= c+dY

Where C= the level of consumption or in this case be treated as the import demand for the product.

c= the level of consumption when the income is zero

d= marginal propensity to consume the product.

Y= the income.

Again from the demand-supply theory of economics, the relationship between the demand and the price of the product can also be traced. As per the theory of demand and supply, the demand for a product is negatively related to the level of the price if the product is not a Giffen good (Florence, 2018). In this case, bread is not a Giffen good as the demand for the product does not increase with the price of the product. Thus, the equation state that,

Qd= e-fP

Where Qd= quantity demanded of the good

e= intercept term

f= slope of the demand curve

P= the price of the product.

Now, the equation of the both the Qd and C can be merged together as in the case of imported bread is equivalent to the consumption demand of bread and get a common model to get a relationship among the import of bread, price and the income of the consumer of the market (Benjamin et al. 2018). Therefore the model becomes,

Ib = β01P+β2Y+ε

Where Ib= import of the bread

P= price of bread

Y= income of the consumers of the market

Ε= error term

And β’s are the coefficients

Following is the data of import of bread since the year 1994, the import prices of the product and the income of the customers of the market. All the values have been converted nullifying the inflation factor taking the base value of the year 2006.

Year

Import of bread (Quintals)

Price of bread($)

Mean income($)

2017

4524

1.06

88420

2016

2548

1.75

84232

2015

3634

1.5

86521

2014

2458

1.72

84125

2013

4582

0.96

86235

2012

2458

1.95

81240

2011

752

2.5

75264

2010

2457

1.85

84562

2009

2456

1.85

84521

2008

2468

1.86

85452

2007

2451

1.91

86521

2006

4685

1

89521

2005

2458

1.81

81250

2004

3658

1.51

86521

2003

2458

1.75

81245

2002

2468

1.75

81456

2001

7546

0.78

87954

2000

2459

1.45

81245

1999

6524

1

87504

1998

4254

1.12

86521

1997

5264

0.96

87565

1996

5242

0.92

87524

1995

2457

1.71

81245

1994

2457

1.76

81253

Table 1: The import, prices and the income of the customers

(Source: )

Therefore the regression analysis is as follows:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.926484

R Square

0.858373

Adjusted R Square

0.844885

Standard Error

621.6201

Observations

24

ANOVA

df

SS

MS

F

Significance F

Regression

2

49181268

24590634

63.63846

1.22E-09

Residual

21

8114642

386411.5

Total

23

57295910

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

3753.664

5954.19

0.630424

0.535218

-8628.75

16136.08

-8628.75

16136.08

Price of bread($)

-3008.31

482.6582

-6.2328

3.5E-06

-4012.06

-2004.57

-4012.06

-2004.57

Mean income($)

0.050408

0.063381

0.795323

0.435324

-0.0814

0.182216

-0.0814

0.182216

Table 2: The multiple regression analysis

(Source: developed by the learner)

Observation

Predicted Import of bread (Quintals)

Residuals

Standard Residuals

1

5021.957838

-497.9578379

-0.838343116

2

2735.110551

-187.1105511

-0.315012297

3

3602.573939

31.42606059

0.052907735

4

2819.966294

-361.9662939

-0.609392859

5

5212.647025

-630.6470246

-1.061733648

6

1982.625813

475.3741867

0.800322129

7

26.81241653

725.1875835

1.220898583

8

2450.913852

6.086148009

0.01024641

9

2448.847109

7.15289087

0.012042338

10

2465.694149

2.3058513

0.003882045

11

2369.164959

81.83504118

0.137774402

12

5257.95632

-572.9563202

-0.964607744

13

2404.293939

53.70606096

0.090417507

14

3572.490794

85.50920646

0.143960089

15

2584.540772

-126.5407724

-0.213039292

16

2595.176937

-127.1769369

-0.214110315

17

5840.795625

1705.204375

2.87081805

18

3487.035148

-1028.035148

-1.73076137

19

5156.282653

1367.717347

2.302637563

20

4745.733482

-491.7334824

-0.827864025

21

5279.690147

-15.69014668

-0.026415342

22

5397.955987

-155.9559873

-0.262561644

23

2704.873356

-247.8733559

-0.417310274

24

2554.860893

-97.86089347

-0.164754925

Table 3: the Residuals of the analysis

(Source: Developed by the learner)

Therefore, as per the result of the regression analysis,

Ib= 3753.66-3008.31*P+0.050*Y

The fit of the model is good as the r square value of the regression is 0.85 which is considered as a good fit.

Therefore, the study shows that how the demand for the imported product is dependent on the prices of the product and the income level of the customers of the market (Camerer et al. 2016). As per the findings of the regression analysis, Price is negatively related to the demand and the income of the customers is positively related to the import demand. In other words, with the increase in the prices of bread the import demand goes down and with an increase in the income, the demand for the bread goes up.  However, it needs to be noted in this case is that the income effect is weaker than the substitution effect (Meyer, 2017). As per the equation provided by the regression analysis, the coefficient of price is very high that means the impact of price change on the demand is more than the changes in the income of the customers.

Data Analysis and Results

Figure 1: The relationship between the prices and the import demand

(Source: developed by the learner)

Figure 2: the relationship between the income and the import demand of the product

(Source: Developed by the learner)

As per the study and the result of the paper, the price changes impacts more than that of the changes in the income of the customers. Therefore, it is recommended to the government to implement a support price for the bread so that the price remains same throughout and hence the demand is would be stable. In addition to that, the companies and the government of the country can also understand from the analysis that, bread is a basic food for the citizen of the country and there is another substitute of the product as well. This can also be the reason for the low responsiveness of the demand for the bread to the changes in the income of the customers.

Thus, the analysis shows that the import demand for bread depends upon two of the independent variables that influence the dependent variable. The independent variables are the prices of the bread and the income of the customers of the market. This has also been shown by the demand-supply theory and the consumption functions of economic literature. The implemented multiple regression analysis shows that the influences of the price over the import demand of the bread are more than the influences of the income of the customers. Therefore, from the side of the government, it is important to undertake policies to provide support prices to the importers in order to stabilise the import of bread in the economy of Kuwait.

References

Benjamin, D.J., Berger, J.O., Johannesson, M., Nosek, B.A., Wagenmakers, E.J., Berk, R., Bollen, K.A., Brembs, B., Brown, L., Camerer, C. and Cesarini, D., 2018. Redefine statistical significance. Nature Human Behaviour, 2(1), p.6.

Camerer, C.F., Dreber, A., Forsell, E., Ho, T.H., Huber, J., Johannesson, M., Kirchler, M., Almenberg, J., Altmejd, A., Chan, T. and Heikensten, E., 2016. Evaluating replicability of laboratory experiments in economics. Science, 351(6280), pp.1433-1436.

Cuomo, R.E., Mackey, T.K. and Stigler, P., 2015. The economics of counterfeit Avastin: a geospatial and statistical analysis of demographic correlates to FDA warning letters. Pharmacoepidemiology and drug safety, 24(7), pp.748-756.

Florence, P.S., 2018. The statistical method in economics and political science: a treatise on the quantitative and institutional approach to social and industrial problems. Routledge.

Fu, M.C., 2016. Handbook of simulation optimization. Springer.

Klamer, A., 2018. Humanism Challenges Materialism in Economics and Economic History.

Leamer, E.E. and Stern, R.M., 2017. Quantitative international economics. Routledge.

Leuven, E. and Sianesi, B., 2018. PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing.

Meyer, J.R., 2017. The economics of slavery: and other studies in econometric history. Routledge.

Pheby, J., 2015. Methodology and economics: a critical introduction. Routledge.

Stiglitz, J.E. and Rosengard, J.K., 2015. Economics of the Public Sector: Fourth International Student Edition. WW Norton & Company.

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My Assignment Help. Causal Relationship Between Prices And Income Of Customers On Import Demand Of Bread In Kuwait [Internet]. My Assignment Help. 2019 [cited 23 July 2024]. Available from: https://myassignmenthelp.com/free-samples/humanism-challenge-materialism-in-economics.

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