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In recent years, labor economists have had renewed interest in the relationship between the job vacancy rate (open but unfilled job postings) and the unemployment rate. This relationship is commonly represented by the "Beveridge Curve" (named after William Beveridge), which has the job vacancy rate on the y-axis and the unemployment rate on the x-axis.
A. You have data on the monthly job vacancy rate and unemployment rate in the U.S. and wish to estimate the Beveridge Curve. Use a graph and a static time series model to estimate the Beveridge Curve using the data provided. Interpret your results and comment on the statistical significance. Does this match the predicted findings for a typical Beveridge Curve, and does this match economic theory/our expectations?
B. Use an FDL model of order 6 to re-estimate your model from part A, again interpreting your results and commenting on the statistical significance. What, if anything, do your results suggest about the issue of long-term unemployment?
C. Do you believe that your models from parts A and B can satisfy the Gauss-Markov assumptions with the data provided? Explain why or why not.
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Event 1: The government passes a law allowing states to pay unlimited unemployment benefits to all unemployed workers for an unlimited amount of time. Event 2: The federal government increases the restrictions on the immigration of skilled workers
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