How to perform unit root test?

By Priya Chetty on September 19, 2018

Unit root indicates a stochastic trend in the time series. Sometimes it is known as “random walk with drift”. A time series dataset will show a systematic unpredictable pattern if it has the unit root. If a time series dataset has the unit root, the regression result will be unreasonable and provide a spurious result (in which there is large r-squared value even if the data is uncorrelated) and errant behavior (in which t-rations will not follow at- distributions). Therefore it is important to perform unit root test.

Problems with unit root

Presence of unit root also causes that series to be non-stationary. A series should be stationary where its statistical properties do not vary with time (expectation, variance, autocorrelation). Stationary data will give better results. The main problems associated with unit roots are:

  • The variance will not be constant
  • Ordinary Least Square (OLS) estimates will be biased.

Therefore, it becomes necessary to perform unit root test and correct unit root.

Using an augmented dickey-fuller test for checking the unit root

In case of serial autocorrelation, Augmented Dickey-Fuller (ADF) test is used to examine the presence of unit root. The null hypothesis for the ADF test is that there is a unit root (means series is non-stationary). Then differencing of the variable is used to make a stationary series (not autocorrelated). The alternative hypotheses are that there is no presence of unit root.

For instance, in the FDI study, the data on FDI is coming out to be non-stationary, which implies that its series do not have a constant mean, constant variance, and constant co-variance over time. Therefore the ADF test was applied to the correct unit root.

Priya is the co-founder and Managing Partner of Project Guru, a research and analytics firm based in Gurgaon. She is responsible for the human resource planning and operations functions. Her expertise in analytics has been used in a number of service-based industries like education and financial services.

Her foundational educational is from St. Xaviers High School (Mumbai). She also holds MBA degree in Marketing and Finance from the Indian Institute of Planning and Management, Delhi (2008).

Some of the notable projects she has worked on include:

  • Using systems thinking to improve sustainability in operations: A study carried out in Malaysia in partnership with Universiti Kuala Lumpur.
  • Assessing customer satisfaction with in-house doctors of Jiva Ayurveda (a project executed for the company)
  • Predicting the potential impact of green hydrogen microgirds (A project executed for the Government of South Africa)

She is a key contributor to the in-house research platform Knowledge Tank.

She currently holds over 300 citations from her contributions to the platform.

She has also been a guest speaker at various institutes such as JIMS (Delhi), BPIT (Delhi), and SVU (Tirupati).

 

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