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Mountain Monitor - 4th Quarter 2013, Kenan Fikri, Mark Muro

Mountain Monitor Quarterly

The quarter’s Mountain Monitor finds that the pace of economic recovery in the Mountain West region’s major metropolitan areas converged toward that of the rest of the nation in the last quarter of 2013.

While quarterly performance on the Monitor’s four indicators of economic recovery—employment, output, the unemployment rate, and house prices—varied considerably across the 10 major metro areas of the region, their combined performance broadly slowed to track with the rate of national economic recovery. The quarter’s average job growth remained unchanged in the region at 0.4 percent as the national economy caught up. The gap between the national …

Mountain Monitor - 3rd Quarter 2013, Kenan Fikri, Mark Muro

Mountain Monitor Quarterly

The quarter’s Mountain Monitor marks the four-year anniversary of Brookings Mountain West's quarterly tracking of the uneven pace of recovery across the major metro areas of the Intermountain West and it finds that, although the region continues to outperform the national economy the rate of recovery slowed moderately in the region’s metro areas.

As a group, Mountain region metro areas advanced on all four indicators of economic recovery tracked by the Monitor—employment, output, unemployment, and house prices—but their progress was more restrained in the third quarter of 2013 than it was in the second.

Beneath the regional headline of moderating …

Mountain Monitor - 2nd Quarter 2013, Kenan Fikri, Mark Muro

Mountain Monitor Quarterly

Economic recovery progressed steadily across the metropolitan Mountain West in the second quarter of 2013. Many of the region’s major metro areas counted among the strongest economic performers nationally, but output growth slowed over the quarter and the region‘s unemployment recovery looked to be stagnating. Moderate job growth and a fast and accelerating housing recovery buoyed the Mountain West economy in the second quarter.

Mountain Monitor-1st Quarter 2013, Kenan Fikri, Mark Muro

Mountain Monitor Quarterly

Economic recovery gained strength across the major metro areas of the Mountain West in the first quarter of 2013. Multiple metro areas achieved long-awaited full employment recoveries in the first quarter and regional production surpassed pre-recession levels of output for the first time. The region’s strong housing rebound continued to be a boon. Additionally, a special supplement to the Monitor shows that the healthcare sector has been an outsized contributor to recovery throughout the region. Despite progress on multiple fronts, though, many Mountain metro areas remain scarred with high unemployment rates, severely depressed house prices, and daunting jobs deficits.

Mountain Monitor-1st Quarter 2011, Mark Muro, Kenan Fikri, Jonathan Rothwell

Mountain Monitor Quarterly

The pace of economic recovery slowed in the large metros of the Intermountain West in the first quarter of 2011. Widespread but slowing output growth was coupled with much slower improvement in the labor market, where for the first time the region’s unemployment rate edged above the nation’s. The weight of a still-depressed housing market slowed recovery further. Overall, the differing courses of the region’s 10 major metro economies since the beginning of the recession can be characterized by relatively strong bouncebacks to the north and east of the region and more sluggish and protracted slogs to the south and …

A Monte Carlo Analysis Of Hedonic Models Using Traditional And Spatial Approaches, Helen R. Neill, David M. Hassenzahl, Djeto D. Assane

Public Policy and Leadership Faculty Publications

Hedonic regression analysis of single family homes typically includes structural variables, locational variables and neighborhood quality characteristics. When nearby properties are related, Dubin (1988) reports that error terms are spatially autocorrelated. Estimation methods for these spatially autocorrelated error terms or hereafter, spatial approaches, include maximum likelihood estimation (MLE) and kriging techniques such as kriged maximum likelihood estimation (KMLE). Unfortunately these spatial methods require massive computer resources and are limited to significantly fewer observations than traditional ordinary least squares (OLS). This paper investigates the combination of spatial approaches and Monte Carlo analysis, a method that approximates large data sets. A question …