Exploring Google Searches And Their Relationship With The Unemployment Rate

Exploring Google Searches And Their Relationship With The Unemployment Rate

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Preliminary Results

Companies like Google or Facebook started as a way to connect people around the globe, one in the form of a search engine and the other simply as a website to keep in contact with friends at the completion of university or after a difficult move. Regardless of how useful one sees either of these companies, online activity, in the form of search engines, social media or the like, has proven itself to be a rich source of information useful in various fields of research. Our study will be focused on Google searches and their relationship with the unemployment rate in two countries, the UK and Poland. If claims are made for the utility of online search activity as a source to look for jobs, its efficiency should be shown not only for developed countries but also for emerging economies.

The monthly unemployment data for the UK has been collected from the UK Office for National Statistics (ONS). Data for Poland however has been collected from the Polish Ministry of Labour & Social Policy. In our analysis we use the raw unemployment rate, meaning that the data is not seasonally adjusted. We use this both of these data because the Google data are not seasonally adjusted either. As the languages of the studies countries differ, we have looked for different terms. For the UK we searched the term “jobs,” while in Poland we opted for the word “praca”, which translates to “jobs” or “work” in English. Each series, both the unemployment rate and the Google searches, are studied between January of 2004 and September of 2016. With monthly data at hand here, this equates to 153 observations.

Analysis of the Data

The unemployment rate of the analyzed countries has followed a largely inconsistent path since 2004, especially i...

... middle of paper ...

...ts for cointegration on our variables shows that there is no cointegration relationship between the unemployment and Google searches, therefore we differenced the series to make the variables stationary. In the analysis, we further proceed with this first differences of the unemployment rate and the first logarithmic differences of the Google searches. This combination of percentage representation and logarithmic transformation also allows for a more straightforward interpretation as a proportional relationship.
To study the relationship between the unemployment rate and the Google searches for the word “jobs”, we will be using the following equation:
where ΔURt and Δlog(GI)t represent the first difference of an unemployment rate at time t and the first logarithmic difference of the Google searches at time t, respectively, for a given country, and εt is an error term.

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