Updated:

Purchasing Power Parity Theory in Statistical Test Report (Assessment)

Exclusively available on Available only on IvyPanda® Made by Human No AI

Introduction

Purchasing power parity (PPP) theory is an integral economic theory, which predicts exchange rates of currencies in a country based on the inflation rates using a regression model. The theory postulates that when inflation rate of a country increases, there is a decrease in exports and an increase in imports, resulting in high exchange rates between two countries. With the use of a regression model, it is possible to assess the validity of the theory in predicting the relationship between exchange rates and differential inflation rates over a period.

To apply the theory, the project selected two countries, namely, the United States and Malaysia, and retrieved historical data of annual inflation rates and annual exchange rates from 1970 to 2016. The project obtained data of annual inflation rates from the World Bank (2017a) and data of annual exchange rates from the World Bank (2017b). Therefore, this project predicts the influence of the annual difference in inflation rates on annual exchange rates using the regression model and compared obtained β0 and β1 values with the ones of the PPP model.

Regression Model Used

The project used the following regression model in predicting the influence of the difference in annual inflation rates on annual exchange rates.

Regression Model Used

Where β0 is the y-intercept, β1 is the gradient, and 6 is the error term.

Regression Outcomes

Table 1 below is a regression model showing the strength of relationship between annual exchange rates and annual inflation rates, and the degree of prediction. The regression model shows that there is a weak relationship between annual exchange rates and the difference in annual inflation rates of Malaysia and the United States (R =0.28). R-square reveals that annual exchange rates account for 7.8% of the variation in the difference in annual inflation rates (R2 = 0.078).

Table 1.

Model Summaryb
ModelRR SquareAdjusted R SquareStd. Error of the Estimate
1.280a.078.058.570156
a. Predictors: (Constant), Difference in Average Annual Inflation Rates
b. Dependent Variable: Average Annual Change in Exchange Rate

The ANOVA table (Table 2) indicates that the regression model is statistically insignificant in predicting the influence of annual exchange rates on the difference in annual inflation rates, F(1,45) = 3.822, p = 0.057.

Table 2.

ANOVAa
ModelSum of SquaresdfMean SquareFSig.
1Regression1.24211.2423.822.057b
Residual14.62845.325
Total15.87146
a. Dependent Variable: Average Annual Change in Exchange Rates
b. Predictors: (Constant), Difference in Average Annual Inflation Rates

Coefficients’ table (Table 3) shows that annual exchange rate is a predictor, which is statistically insignificant in predicting the difference in inflation rates between the United States and Malaysia (p = 0.057).

Table 3.

Coefficientsa
Unstandardized CoefficientsStandardized CoefficientstSig.95.0% Confidence Interval for B
ModelBStd. ErrorBetaLower BoundUpper Bound
1(Constant)2.005.08523.468.0001.8332.177
Difference in Average Annual Inflation Rates.065.033.2801.955.057-.002.133
a. Dependent Variable: Average Annual Change in Exchange Rate

Equation of the Regression Model

Equation of the Regression Model

Testing of the PPP Theory

Graphical Test

The graphical test provides a visual and conceptual way of testing the PPP theory using empirical data. Figure 1 is a scatterplot depicting the relationship between annual exchange rate and the difference in inflation rates for Malaysia and the United States. The scatter plot shows that there is apparent deviation of data points and trend line from the PPP line. The deviation implies that the PPP theory does not hold in explaining the variation of exchange rates based on trends of inflation rates from 1970 to 2016. According to Baumol and Blinder (2015), a graphical depiction of relationships between exchange rates and the difference in inflation rates shows if data points differ considerably from the trend line of the PPP model.

Exchange rate versus difference in inflation rate

Statistical Test

Regression model shows that coefficient of β0 = 2.005 while the coefficient of β1 = 0.065. The t-test aims to determine if the coefficients of the regression model differ significantly from the coefficient of the PPP model, which has β0 of zero and β1 of one. Madura (2016) explains that coefficients of the regression model and their respective standard errors are values used in the t-test analysis to determine the significance of the difference from the hypothesized values of the PPP model.

At β0 = 0, t =β0 – 0/ SE = 2.005-0/0.085 = 23.588.

At β1 = 1, t = β1 -1/SE = 0.065 -1/0.033 = -28.33.

Therefore, the t-test rejects the null hypothesis that the coefficients of the regression model are equal to those of the PPP model. In this view, the PPP model is not applicable in predicting inflation of Malaysia based on the trends of the exchange rate of the foreign.

Conclusion

Comparison of the findings and the PPP model shows that there are marked differences in trends as demonstrated by the scatterplot and the statistical test. The findings mean that the PPP model does not hold in predicting the relationship between the annual exchange rates and the annual difference in inflation rates. Suggestively, confounders could have mediated the relationship between the exchange range and the difference in the inflation rate, resulting in observed deviation from the PPP model.

References

Baumol, W., & Blinder, A. (2015). Economics: Principles and policy. New York, NY: Cengage Learning

Madura, J. (2016). International financial management. New York, NY: Cengage Learning.

World Bank. (2017a). . Web.

World Bank. (2017b). . Web.

More related papers Related Essay Examples
Cite This paper
You're welcome to use this sample in your assignment. Be sure to cite it correctly

Reference

IvyPanda. (2020, November 18). Purchasing Power Parity Theory in Statistical Test. https://ivypanda.com/essays/purchasing-power-parity-theory-in-statistical-test/

Work Cited

"Purchasing Power Parity Theory in Statistical Test." IvyPanda, 18 Nov. 2020, ivypanda.com/essays/purchasing-power-parity-theory-in-statistical-test/.

References

IvyPanda. (2020) 'Purchasing Power Parity Theory in Statistical Test'. 18 November.

References

IvyPanda. 2020. "Purchasing Power Parity Theory in Statistical Test." November 18, 2020. https://ivypanda.com/essays/purchasing-power-parity-theory-in-statistical-test/.

1. IvyPanda. "Purchasing Power Parity Theory in Statistical Test." November 18, 2020. https://ivypanda.com/essays/purchasing-power-parity-theory-in-statistical-test/.


Bibliography


IvyPanda. "Purchasing Power Parity Theory in Statistical Test." November 18, 2020. https://ivypanda.com/essays/purchasing-power-parity-theory-in-statistical-test/.

If, for any reason, you believe that this content should not be published on our website, please request its removal.
Updated:
This academic paper example has been carefully picked, checked and refined by our editorial team.
No AI was involved: only quilified experts contributed.
You are free to use it for the following purposes:
  • To find inspiration for your paper and overcome writer’s block
  • As a source of information (ensure proper referencing)
  • As a template for you assignment
1 / 1