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Local Polynomial Regressions versus OLS for Generating Location Value Estimates: Which is More Efficient in Out-of-Sample Forecasts?
As an alternative to ordinary least squares (OLS), we estimate location values for single family houses using a standard housing price and characteristics dataset by local polynomial regressions (LPR), a semi-parametric procedure. We also compare the LPR and OLS models in the Denver metropolitan area in the years 2003, 2006 and 2010 with out-of-sample forecasting. We determine that the LPR model is more efficient than OLS at predicting location values in counties with greater densities of sales. Also, LPR outperforms OLS in 2010 for all 5 counties in our dataset. Our findings suggest that LPR ...
So, Why Didn’t the 2009 Recovery Act Improve the Nation’s Highways and Bridges?
Although the American Recovery and Reinvestment Act of 2009 (the Recovery Act) provided nearly $28 billion to state governments for improving U.S. highways, the highway system saw no significant improvement. For example, relative to the years before the act, the number of structurally deficient or functionally obsolete bridges was nearly unchanged, the number of workers on highway and bridge construction did not significantly increase, and the annual value of construction put in place for public highways barely budged. The author shows that as states spent Recovery Act highway grants, many ...
The Road of Federal Infrastructure Spending Passes Through the States
Because federal infrastructure spending largely takes the form of grants to state governments, the macroeconomic impact of such packages depends on the share of federal grants that “passes through” to actual infrastructure spending done by states. A low degree of pass-through would tend to mute the economic impact from federal grants, reflecting a crowd-out effect on state spending. We first revisit Knight’s (2002) influential finding of near-zero pass-through (perfect crowd out) of federal highway grants. That result is found to be specification-sensitive and is reversed completely in ...
Semi-Parametric Interpolations of Residential Location Values: Using Housing Price Data to Generate Balanced Panels
We estimate location values for single family houses by local polynomial regressions (LPR), a semi-parametric procedure, using a standard housing price and characteristics dataset. As a logical extension of the LPR method, we interpolate land values for every property in every year and validate the accuracy of the interpolated estimates with an out-of-sample forecasting approach using Denver sales during 2003 through 2010. We also compare the LPR and OLS models out-of-sample and determine that the LPR model is more efficient at predicting location values. In a balanced panel application, we ...
Migration, Congestion Externalities, and the Evaluation of Spatial Investments
The direct benefits of infrastructure in developing countries can be large, but if new infrastructure induces in-migration, congestion of other local publicly provided goods may offset the direct benefits. Using the example of rural household electrification in South Africa, we demonstrate the importance of accounting for migration when evaluating welfare gains of spatial programs. We also provide a practical approach to computing welfare gains that does not rely on land prices. We develop a location choice model that incorporates missing land markets and allows for congestion in local land. ...
A Narrative Analysis of Federal Appropriations for Research and Development
This paper provides a narrative analysis of postwar federal appropriations for the research and development (R&D) activities of the Department of Defense, Department of Energy, National Aeronautics and Space Administration, National Institutes of Health and National Science Foundation—five agencies that consistently account for the vast majority of federal outlays for all types of R&D. We build a novel dataset quantifying the enacted full-year appropriations for all budgetary accounts funding R&D activities at these five agencies over fiscal years 1947-2019. We use this dataset to isolate a ...