1. Plot ef,t against (IDC,t – IFC,t).
Check if the plot forms a 45 degree line -i.e., the PPP line.2. Determine PPP
exchange rates. Graph PPP exchange rates along St. Based on your
(visual) findings, clearly state if PPP captures the short-run and/or long-run
behavior of St. 3. Using the whole sample, run a linear regression.
Dependent variable: ef,t. Independent variable: (IDC,t –
IFC,t). Null hypothesis to test: α=0 and β=1. (Note: you can use any
software of your choice to run the regression. If you want to run regressions
in Excel, you can simply google and find out how to run regressions in Excel.) Clearly
state if you reject or cannot reject PPP. 4. Write a brief paragraph with your views aboutthe PPP Model.
Unformatted Attachment Preview
Project: Testing the purchasing power parity (PPP) theory
Billy Bull Fund specializes in investing in emerging markets. One country of interest is Turkey.
Because of the high inflation in Turkey during 1960-2004, the Turkish Lira : U.S. Dollar
exchange rate increases from an average of 9 lira per U.S. dollar in the late 1960s to
approximately 1.65 million lira per U.S. dollar in late 2001. However, since the introduction of
new lira in 2005, dropping 6 zeros from the old lira, the Turkish currency has stabilized
significantly in recent years. Due to the extremely volatile Turkish exchange rates in the last
century, Billy is concerned and would like to explore whether inflation is the driver of the
volatile exchange rates. One theory linking inflation and exchange rate is the PPP. Billy wants to
know whether PPP holds or to what extent PPP holds.
The rate of change in (index) prices should be similar when measured in a common currency.
(As long as trade frictions are unchanged).
Here is the linear relative PPP model: ef,t = (IDC,t – IFC,t).
We can test the relative PPP using a regression based on the relative PPP model:
ef,t = α + β (IDC,t – IFC,t) + εt
Under the relative PPP, the hypothesis to test is: H0: α=0 and β=1.
You have monthly Consumer Price Indexes (CPI) and exchange rates (St) from the following
Exchange rates: http://fx.sauder.ubc.ca
Consumer price indexes: I suggest the following website:
1). You can specify the time & Frequency to monthly and choose your time periods for at least
the last 5 to 10 years (2008 to 2018).
2). You can then click on the fourth icon above to export the data into an excel file.
3). Select the country of interest, you can then select the data for that country and post into a new
spreadsheet using paste special and choose transpose. This way you can transform the data from
rows into columns.
CPI for the U.S.: http://www.bls.gov/cpi/
CPI for other countries can be obtained from World Bank, IMF, or other sources.
CPI and Exchange Rates are in levels. Thus, you need to put the data into percentage changes to
test relative PPP. That is, you need to create ef,t, IFC,t, and IDC,t.
Here is an example of transforming data from levels to percentage changes.
Things to Do
1. Plot ef,t against (IDC,t – IFC,t). Check if the plot forms a 45 degree line -i.e., the PPP line.
2. Determine PPP exchange rates. Graph PPP exchange rates along St. Based on your (visual)
findings, clearly state if PPP captures the short-run and/or long-run behavior of St.
3. Using the whole sample, run a linear regression. Dependent variable: ef,t. Independent
variable: (IDC,t – IFC,t). Null hypothesis to test: α=0 and β=1. (Note: you can use any software of
your choice to run the regression. If you want to run regressions in Excel, you can simply google
and find out how to run regressions in Excel.) Clearly state if you reject or cannot reject PPP.
4. Write a brief paragraph with your views about the PPP Model.
Tips: Running a Regression
• Do not forget that the regression uses percentage changes. That is, before doing the regression,
you need to calculate ef, and IDC, IFC
• Excel has a regression wizard (Analytical ToolPak), which students have found very helpful
and easy to use. But, any regression package -Excel, SAS, SPSS, etc.- will estimate the
coefficients and also calculate R2, SSR, F-stat and t-statistics.
• In Excel, on the Tools menu, click Data Analysis. (If Data Analysis is not available, load the
Analysis ToolPak.) On the Data Analysis dialog box, click regression, then click OK. Input ef as
your Y variable. Input (IDC-IFC) as your X variable.
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