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Searching for the Output Gap

Longbrake, Mark William

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2008, Doctor of Philosophy, Ohio State University, Economics.

This dissertation investigates the usage and estimation of the output gap. The wide use of the output gap as a variable in the monetary policy literature makes learning more about the output gap necessary. The biggest issue with the output gap is that although it is a straightforward theoretical concept it can not be observed directly, meaning it must be estimated. The economics literature currently estimates the output gap by three different methods. The first is direct detrending of the GDP data, the second is indirect estimation, and the third is the production function approach. This dissertation uses both the first and the third methods in order to produce an output gap estimate that is theoretically and econometrically attractive.

We begin by investigating the long term trend in US real GDP directly from the GDP data using a new econometric technique, Adaptive Least Squares (ALS). ALS is a special case of the Kalman Filter that allows for a time varying parameter model to be estimated relatively easily. The estimated trend is then used to estimate the output gap. The results of our estimation suggest that GDP does not follow even a time-varying long term trend, so the output 'gap' as specified is illusory.

Chapter 3 derives both an unemployment gap and a capacity utilization gap, using Adaptive Least Squares (ALS), and combines them to formulate our Factor Utilization Model. The use of both unemployment and capacity utilization allows us to consider the effects of both labor and capital under or over utilization, thus eliminating a potential substitution bias from the unemployment gap, and avoiding unit root problems from a univariate estimation of the output gap. Additionally the fact that the Factor Utilization Model can be estimated monthly allows for more frequent data availability.

Our final chapter compares various estimates of the output gap including all of the estimates developed earlier. We group the output gap estimates into three broad categories, one-sided filters two-sided filters and real-time estimates. Two-sided filters use the entire history of the data in order to arrive at an estimate. This means that they are very useful for looking backwards at the economy to determine how things were, but they are of little use in saying what would, or should have been done in the past. One-sided filters only use the data from periods up to and including the period being estimated. This gives the estimate that would have been generated if the estimation was being done historically. The final group of estimates utilizes real-time data. This is the data as it was initially published before it was subsequently revised. We find that the GDP data and the Congressional Budget Office's estimate of the output gap are subject to large ex post revisions, but that the unemployment and capacity utilization data are not. This lends strength to our Factor Utilization Gap as our output gap proxy of choice.

J. Huston McCulloch, PhD (Advisor)
Pok-sang Lam, PhD (Committee Member)
Paul Evans, PhD (Committee Member)

Recommended Citations

Citations

  • Longbrake, M. W. (2008). Searching for the Output Gap [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1217970053

    APA Style (7th edition)

  • Longbrake, Mark. Searching for the Output Gap. 2008. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1217970053.

    MLA Style (8th edition)

  • Longbrake, Mark. "Searching for the Output Gap." Doctoral dissertation, Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1217970053

    Chicago Manual of Style (17th edition)