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PROJECT TITLE Weekly initial claims for unemployment in the US and google search data.
One of the strongest leading indicators of economic activity is the number of people who file for unemployment benefits. It appears that many economists, market participants, policymakers, andfinancial markets pay particularly close attention to the report on initial unemployment insurance claims. The reason,in short, is that changes in labor market activity are thought to be useful predictors for changes in real gross domestic product (GDP), the broadest measure of economic activity. Google Trends/Search Insights data could be useful in short term predictions of economic variables. Given the importance of initial claims as a macroeconomic predictor, it would be useful to try to forecast this economic metric. The initial claims data is available from the Department of Labor, while the Google Trends data for relevant categories is available in google correlate. We applied the methodology outlined in our earlier paper, building a model to forecast initial claims using the past values of the time series, and then added the Google Trends variables to see how much they improved the forecast.
The objective is to predict the rate of weekly initial claims for unemployment using google search keywords.
DATA: The Federal Reserve Economic data set was obtained from economic research division of Federal Reserve Bank of St Louis. The data consist of the weekly initial claims for unemployment insurance in the US, as reported by the US Federal Reserve. For economic decisions based on these and similar numbers, it would help to have an early forecast of the current week's number as of the close of the week.
ANALYSIS: Linear Regression prediction was used for the modelling. For economic decisions based on these and similar numbers, it would help to have an early forecast of the current week's number as of the close of the week.